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Speaker 1: Brought to you by the reinvented two thousand twelve Camray.

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Speaker 1: It's ready. Are you get in touch with technology with

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Speaker 1: tex Stuff from how stuff works dot com. Hello, and

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Speaker 1: welcome to tex Stuff. My name is Chris Poulette and

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Speaker 1: I am an editor at how stuff works dot com,

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Speaker 1: sitting in a cross froom me as usual as senior

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Speaker 1: writer Jonathan Strickland. Psychics can see the color of time.

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Speaker 1: It's blue. Okay, I'd kind of love to know what

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Speaker 1: what that one's from. I'll tell you. I'll tell you

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Speaker 1: after the show if you remind me, alright, I always

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Speaker 1: say that I'll tell you, and I never tell you

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Speaker 1: because I always forget by the time we're done recording.

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Speaker 1: Tell me what there's the trivia for you, folks. So

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Speaker 1: today we thought we would look at something. Actually, it

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Speaker 1: was Chris's suggestion that we look into this particular topic,

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Speaker 1: which was the the topic of image sensors and what

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Speaker 1: they do and what the two main types of image sensors,

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Speaker 1: how they are different from one another, and uh, and

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Speaker 1: I thought it was a great idea. It's also a

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Speaker 1: fairly complex topic. We do have an article on how

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Speaker 1: stuff works dot com that says what is the difference

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Speaker 1: between c c D and CMO s image sensors in

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Speaker 1: a digital camera. And that's really what we're gonna be

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Speaker 1: talking about here. Um. So that there is an article

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Speaker 1: on the site, and it's a nice short article if

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Speaker 1: you want a quick overview, but we're gonna go into

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Speaker 1: some detail a little bit in this podcast. And really

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Speaker 1: the first thing you need to know is that an

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Speaker 1: image sensor is it's taking the place of film, right, Yes,

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Speaker 1: that's correct. Yeah, a long and long time ago in

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Speaker 1: a galaxy that happens to be right here where we're sitting.

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Speaker 1: We did a podcast on the megapixel myth um. I

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Speaker 1: think a lot of people equate uh numbers with a

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Speaker 1: way too yeah, with quality, and they say, oh, well,

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Speaker 1: I've got a twelve megapixel camera that's obviously better than

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Speaker 1: that six make a pixel camera I used to own. Well,

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Speaker 1: it depends on what you're doing with the photo. It

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Speaker 1: also depends on again the other qualities of that camera, right,

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Speaker 1: and image sensors have a lot more to do with

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Speaker 1: the quality of the photo. But in a way it

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Speaker 1: really depends because again this uh there, there's this this

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Speaker 1: idea that there are two different kinds which kind is better.

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Speaker 1: It depends on what you're doing with that, what are

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Speaker 1: you taking photos of? UM and uh, as it turns out,

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Speaker 1: they're they're not really better than one another. Inherently, they're

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Speaker 1: they're better than one another for specific applications of the

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Speaker 1: photographic technology, and the quality of the two sensors is

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Speaker 1: constantly getting closer and closer, so that the things that

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Speaker 1: one sensor does better than the other start to become

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Speaker 1: less distinct over time because the technology is improving on

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Speaker 1: both sides simultaneously. Uh. If we were to go back

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Speaker 1: a little bit to the early days of digital cameras,

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Speaker 1: the distinction was was clear. You know, you would say that, well,

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Speaker 1: a professional photographer would more likely have a cc D

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Speaker 1: image sensor in his or her camera c c D

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Speaker 1: meaning charge coupled device, charge coupled device, that's that's one

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Speaker 1: of the two types. And someone who has say a

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Speaker 1: relatively inexpensive of course, back in the early day of

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Speaker 1: digital cameras, that was definitely relatively eight billion dollars, only

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Speaker 1: a thousand, princely going back to that a thousand dollars

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Speaker 1: as opposed to say eight thousand dollars. But a person

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Speaker 1: holding one of those cameras might have a CMOS or

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Speaker 1: a complementary metal ox side semiconductor image sensory. They come

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Speaker 1: up and say, that's a wonderful shirt you're wearing today.

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Speaker 1: That's such a great picture you've taken. Have you lost weight? No,

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Speaker 1: it's not that kind of complimentary. I have a whole

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Speaker 1: joke about that, but I'm going to everybody because we've

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Speaker 1: already said the punchline. Anyway, these are the two different sensors,

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Speaker 1: and they do go about capturing data a different way.

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Speaker 1: Let's let's go into the basic way a camera captures

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Speaker 1: an image. I'm going to talk about still camera here. Okay,

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Speaker 1: so we're talking about cameras in general, not necessarily film

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Speaker 1: or digital. Right, So, in general, what happens is you've

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Speaker 1: got a camera and you're pointing it at something that

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Speaker 1: you want to take a photo of. Light is coming

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Speaker 1: towards you. It's reflecting off of the the subject of

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Speaker 1: your photo. If light we're not reflecting off the subject

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Speaker 1: of your photo, it would either mean you were in

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Speaker 1: total darkness, in which case taking a photo is not

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Speaker 1: very helpful, or you're taking a picture of a black

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Speaker 1: hole because not even light can escape it. That being said,

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Speaker 1: they're actually looking at making a physical picture of a

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Speaker 1: black hole using radio telescopes, which is so cool. That's

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Speaker 1: a tangent. Anyway, so light is coming from the subject

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Speaker 1: is some We should do a full podcast just on that.

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Speaker 1: But anyway, lights coming from from the subject towards the

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Speaker 1: camera and uh, and the light passes through the lens.

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Speaker 1: The purpose of the lens is to focus that light

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Speaker 1: toward a specific point within the camera. It moves through

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Speaker 1: the aperture, which is the opening behind the lens that

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Speaker 1: allows light to pass through. There's a shutter that's there

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Speaker 1: behind the aperture which actually directs the light up towards

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Speaker 1: the view finder. For the old style cameras, you know,

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Speaker 1: the ones that don't have the you know, you're not

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Speaker 1: looking at a screen on the back, you're looking actually

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Speaker 1: through a view finder. Well, that light gets directed up

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Speaker 1: by a mirror that's essentially attached to the shutter that

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Speaker 1: makes the light go up inside the camera. Then it

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Speaker 1: hits a prism which inverts the light. Because you may

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Speaker 1: not know this, but the light the image that's coming in.

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Speaker 1: That's saying the sensor is actually upside down from our perspective. Gasp.

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Speaker 1: So if you didn't have that prism there, the subject

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Speaker 1: you're looking at would be upside down. It would be

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Speaker 1: like everything you're taking photos of was in Australia, unless

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Speaker 1: you're Australian, in which case it's all in Detroit. So

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Speaker 1: that's that's way. If you're wondering why there's all these

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Speaker 1: giant car factories in Australia, it's not. It's just because

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Speaker 1: you didn't have that there, right, Um, Okay, that's a

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Speaker 1: terrible joke, but no, the prism does invert the light,

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Speaker 1: so otherwise again upside down. So when you press the

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Speaker 1: button to capture an image, the shutter, the shutter release exactly,

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Speaker 1: the shutter, the shutter moves out of the way. Instead

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Speaker 1: of the light hitting that mirror and going up to

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Speaker 1: the prism and inverting the light hits either film in

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Speaker 1: a film camera or an image sensor in a digital camera.

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Speaker 1: So really the shutter just moves out of the way

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Speaker 1: and then the light hits the sensor and then you're

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Speaker 1: good to go. It's a little different with the digital

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Speaker 1: cameras that are out right now, but that's in general

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Speaker 1: how the process works. The basics. Yeah, now, and with

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Speaker 1: cameras now, light maybe hitting the sensor constantly, and the

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Speaker 1: shutter itself is not a physical shutter. It's just the

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Speaker 1: way that the sensory captures data. And we'll talk about

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Speaker 1: that when we get to that point. There are two

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Speaker 1: different major types of shutters that we can talk about.

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Speaker 1: So that's the general process. Now, with film, it's a

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Speaker 1: chemical process. Light hits the film and then some chemical

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Speaker 1: reactions take place, and that's what allows you to capture

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Speaker 1: an image. Right. With image sensors, it's not chemical, it's electrical. Right,

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Speaker 1: you're converting light energy into an electronic signal, yes, which

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Speaker 1: then you're gonna want to store to some medium. Yes, uh,

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Speaker 1: you know, typically some kind of flash memory device, depending

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Speaker 1: on on what kind of camera you have. You know,

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Speaker 1: there were some I think that that stored on CD,

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Speaker 1: so you know, your mileage may vary, but in general,

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Speaker 1: some sort of flash device on on today's cameras. Yeah,

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Speaker 1: the old digital camcorders could record on on different kinds

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Speaker 1: of media and so, and digital camcorders are working under

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Speaker 1: the same general principles as digital still cameras, with some

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Speaker 1: you know, other differences, but we'll talk about that. Like

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Speaker 1: I said, so now we get into the differences between

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Speaker 1: the two major types of sensors, the charge coupled device

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Speaker 1: and the complementary metal oxide semiconductor. So we're just gonna

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Speaker 1: go do cc D and CMOS from here on out,

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Speaker 1: I think, otherwise I'm just going to have tongue twisters

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Speaker 1: for the rest of the podcast. Yes, well, I just

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Speaker 1: wanted to make sure that people knew what it what

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Speaker 1: it stood for, obviously very important. So in in a

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Speaker 1: CCD sensor, every single pixel now, pixel, remember, is a

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Speaker 1: point of light. An image is made up of pixels,

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Speaker 1: millions of pixels. That's where the megapixel comes from. Right,

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Speaker 1: So a twelve megapixel camera is going to take twelve

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Speaker 1: megapixels worth of pixels and within the dimensions of that image,

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Speaker 1: whereas an eight megapixel camera will use fewer pixels for

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Speaker 1: that same size. Right. But and that's where our idea

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Speaker 1: about resolution comes in. Sometimes you hear people talk about

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Speaker 1: a low resolution image, it may be that it's got

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Speaker 1: fewer pixels in that image so that you can actually

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Speaker 1: start seeing if if the pixels are large enough and

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Speaker 1: few enough, you can start seeing the borders from one

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Speaker 1: pixel to the next. It's not very smooth, it's almost jagged. Well, yeah,

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Speaker 1: I mean that this is the benefit of having a

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Speaker 1: high megapixel camera. If you shoot it high quality, then

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Speaker 1: you are capturing more more pixels for a specific region

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Speaker 1: of the image, and you can you can render that

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Speaker 1: photo in a larger format. Um because when you shrink,

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Speaker 1: when you when you compress the size of a photo

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Speaker 1: and reduce it in size um, the computer is able to,

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Speaker 1: you know, throw out unnecessary information and that the image

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Speaker 1: still is pretty good looking. When you try to increase

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Speaker 1: the size, the computer has to sort of guess on

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Speaker 1: you know, pixel by pixel basis. Well, I mean, this

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Speaker 1: color is sort of a brown color. It looks like

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Speaker 1: I could throw something else in here similar. And that's

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Speaker 1: why when you increase the size of a photo, a

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Speaker 1: digital photo, that it starts to look kind of jaggedy

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Speaker 1: and rough because the computer is having to guess at

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Speaker 1: what that information is. So if you take a ten

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Speaker 1: megapixel photo and shrink it down, it's it's gonna look

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Speaker 1: pretty good. But if you try to take a two

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Speaker 1: megapixel photo and blow it up, it's not gonna be

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Speaker 1: so pretty. Yeah. If you think about it like a puzzle,

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Speaker 1: Let's say that you have a puzzle that has four

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Speaker 1: pieces to it, well, then you're gonna be able to

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Speaker 1: see the division of those those four pieces very clearly.

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Speaker 1: If it has four million pieces, then it's each of

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Speaker 1: those pieces are individually much tinier than those for giant ones.

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Speaker 1: And so the other issue is that the larger you

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Speaker 1: blow something up, if it's if it doesn't have enough

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Speaker 1: mega pixels in it, not megapixels, but enough pixels, then

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Speaker 1: you're gonna start to notice. But that being said, uh,

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Speaker 1: the general digital cameras that are out there for the

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Speaker 1: consumer market and the general way the consumers use digital cameras,

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Speaker 1: megapixels really don't matter because most of us are not

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Speaker 1: blowing images up to poster size. Most of us are

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Speaker 1: using them for online photo albums. We might print a

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Speaker 1: few out, but usually eight by ten tends to be

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Speaker 1: about the largest because most people don't have printers capable

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Speaker 1: of printing at a larger size, take it to somebody

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Speaker 1: to have it printed. It's kind of expensive, so a poster.

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Speaker 1: Most of us don't do that, So most of us

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Speaker 1: don't need to worry about megapixels at this point. Professional photographers,

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Speaker 1: it's a different story. So cc D sensor each of

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Speaker 1: those pixels has a charge. The photons that are coming

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Speaker 1: in and hitting that image sensor are being transferred from

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Speaker 1: from a light inner g from photons into electrons. Now UH,

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Speaker 1: they have UH there's an output node with a c

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Speaker 1: c D sensor where that is converted into voltage. It's

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Speaker 1: buffered and then sent to a different part of the

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Speaker 1: camera so that it will become an analog signal. So

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Speaker 1: a c c D sensor it's a very it's a

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Speaker 1: very UH specific device that doesn't it doesn't have a

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Speaker 1: lot of other functionality to it apart from the fact

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Speaker 1: that it's taking in light and converting it into voltage. UH.

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Speaker 1: Now the pixel is completely devoted to capturing light and

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Speaker 1: it has a very uniform output. So the that's that's

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Speaker 1: sort of where the the idea of CCD being high

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Speaker 1: quality came from. UH. It was very good at capturing

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Speaker 1: the true essence of whatever it is you're pointing your

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Speaker 1: camera at. You don't have to have you don't have

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Speaker 1: to worry about low lighting effects that kind of stuff,

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Speaker 1: or or having uh an image turn out too grainy

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Speaker 1: if the light is too low, which can happen with

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Speaker 1: CMOS images, particularly from a few years ago. It's a

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Speaker 1: depending on where you know where the manufacturer for your

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Speaker 1: camera got the c m O S sensor. Uh, you

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Speaker 1: might not have as big an issue taking low lighting

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Speaker 1: up images. But if you've ever used a digital camera

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Speaker 1: in a you know, either a dark or just a

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Speaker 1: dem environment, and you look like this just doesn't look good. Now,

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Speaker 1: when I take a photo outside in the middle of

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Speaker 1: the daytime, it looks gorgeous, beautiful colors, very very distinct um.

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Speaker 1: That's part of the problem is that the CMOS sensor

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Speaker 1: captures it in a different way. In that case, every

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Speaker 1: single pixel has its own charge to voltage conversion. The

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Speaker 1: c c D it's doing all of the pixels at once,

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Speaker 1: and c m OS it's doing each pixel individually. And

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Speaker 1: then the sensor itself has other elements added to it

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Speaker 1: that the c c D sensor does not have. Remember

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Speaker 1: we said c c D kind of offloads the information

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Speaker 1: once it's been converted into electrical impulses to other chips, right, Well,

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Speaker 1: those elements are actually on a CMO S sensor. So

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Speaker 1: it's got amplifiers, it's got digitization circuits, so it's actually

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Speaker 1: converting the electricity into bits on the sensor itself. It's

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Speaker 1: got noise reduction capabilities. And so that means that it

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Speaker 1: actually speeds up the process and it decreases the amount

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Speaker 1: of space you need within a camera because all of

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Speaker 1: those elements are found on a single chip as opposed

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Speaker 1: to having dedicated chips for these these specific functions. Unfortunately,

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Speaker 1: also reduces the amount of space it has for image

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Speaker 1: capture because all that stuff is on the same chip. Yes,

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Speaker 1: so that that you know, that's a downside of it, Yes,

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Speaker 1: so you that was one of the arguments again early on,

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Speaker 1: was that c c D cameras could take sharper photos

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Speaker 1: than CMOS cameras, and that you know, it's almost there

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Speaker 1: was also an expense issue, right, c c D image

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Speaker 1: sensors tend to be more expensive than c MS ones CMOS.

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Speaker 1: The process of manufacturer got so efficient that the price

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Speaker 1: started to come down, and that that's why those are

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Speaker 1: the sort of image sensors that you find in things

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Speaker 1: like smartphones. You know, smartphones that have cameras tend to

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Speaker 1: have CMOS sensors in them. They take up less space,

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Speaker 1: they put out less heat, they take less energy to

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Speaker 1: run um and they're very fast. So those are all

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Speaker 1: the qualities that people who are having a who wants

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Speaker 1: something in a nice slim form factor or if that's

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Speaker 1: what's important to them. So yeah, CCDC image sensor might

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Speaker 1: take a sharper quality photo in certain situations, but it's

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Speaker 1: also going to require a larger form factor, and it

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Speaker 1: does take more energy to run, and that that energy

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Speaker 1: is going to also mean more heat because as we know,

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Speaker 1: as electricity runs through a circuit, one of the by

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Speaker 1: products is heat. We haven't figured out a way to

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Speaker 1: get around that yet. It's just one of those one

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Speaker 1: of those realities that it's uh um. Basically it's inefficient

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Speaker 1: enough where some of the energy is being converted to

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Speaker 1: heat energy instead of you know, what it is intended for.

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Speaker 1: So so now we've got down to the the idea

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Speaker 1: of these two different image sensors capturing uh information in

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Speaker 1: different ways um, and the fact that over time both

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Speaker 1: both types of sensors have developed to the point where

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Speaker 1: the differences between the two, apart from the fundamental difference

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Speaker 1: of how they collect information, have started to to diminish. Right,

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Speaker 1: so that you can find some professional cameras out there

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Speaker 1: now that you CMOS image sensors, whereas you know, a

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Speaker 1: few years ago that was really unheard of, and you

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Speaker 1: can also find some consumer cameras, especially in the cam

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Speaker 1: Quorter realm, that are using cc D image sensors, which

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Speaker 1: again for a while you just didn't hear about because

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Speaker 1: c c D cameras were so expensive. It was pretty

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Speaker 1: much reserved for professionals, you know, just consumers just didn't

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Speaker 1: necessarily have the money to drop on something like that

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Speaker 1: unless they were you know, one per centers. So yeah,

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Speaker 1: it's it's it's it's still a developing thing and we're

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Speaker 1: still seeing that kind of level out. But that and

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Speaker 1: the two technologies do still exist. They coexist, so it's

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Speaker 1: not like one has been abandoned on top of in

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Speaker 1: favor of the other, although that tends to their bit,

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Speaker 1: there's usually someone predicting that every few years. Well sure sure,

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Speaker 1: um yeah. A lot of the research that I did

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Speaker 1: for the podcast was from Teleedian Do also which makes

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Speaker 1: which makes both types of sensors, and they had some

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Speaker 1: really interesting, uh comparative white papers and other information if

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Speaker 1: you're interested in getting into the depths of it. It

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Speaker 1: got some of it got fairly complicated, um, but basically

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Speaker 1: they had one paper that said that they're the image

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Speaker 1: sensors can be measured on basically eight different characteristics UM.

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Speaker 1: And these were responsivity, you know, basically how responsive that

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Speaker 1: the sensor is. Uh, it's dynamic range, uniformity, shuttering, UM, speed, windowing,

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Speaker 1: and anti blooming UM. And you know, again this is

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Speaker 1: kind of you know complex, but the the UH, it's

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Speaker 1: kind of funny because the way that the image sensor

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Speaker 1: cap information UM, you know, depending on the type that

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Speaker 1: you're talking about, they're not really uh, it's really application specific.

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Speaker 1: UM some of them. Some of them really don't have

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Speaker 1: that much difference over the others. Like, for example, UM,

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Speaker 1: CMOS chips are known to be a little bit more responsive. UM.

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Speaker 1: But c c D s are have an advantage in

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Speaker 1: dynamic range. But basically they didn't say, you know, the

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Speaker 1: this one chip is better than the others. They said

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Speaker 1: it has more to do with the manufacturing capability and

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Speaker 1: whether the chip has done right and is used in

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Speaker 1: their correct setting than it does UM, you know, for

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Speaker 1: a particular type of technology. Right. And you were mentioned

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Speaker 1: mentioning the fact that there are different shutters. In general,

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Speaker 1: a CMOS image sensor uses a rolling shutter. UH. There's

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Speaker 1: nothing saying that it couldn't use the same sort of

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Speaker 1: shutter that sc D image sensor does, which is a

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Speaker 1: global shutter. There's nothing saying that it couldn't. It's just

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Speaker 1: that all the camcorders I looked at specifically because this

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Speaker 1: really plays more into video than than uh, still photography.

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Speaker 1: Although there's some crossover between the two. Um it said

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Speaker 1: that you could have a CMOS with a global shutter.

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Speaker 1: It's just that you don't find those so once they're

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Speaker 1: between the global shutter and a rolling shutter, well, a

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Speaker 1: rolling shutter to me, when I the first I read

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Speaker 1: about this, the first thing I thought about was, UM

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Speaker 1: a copier or a scanner where the image sensor you

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Speaker 1: put the document on the on the screen, you close

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Speaker 1: the UM the top the lid, and you tell it

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Speaker 1: to go ahead and make a copy or make a

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Speaker 1: scan of it, and the image sensor travels down the

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Speaker 1: length of the document from the top to the bottom

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Speaker 1: or you know however exactly and and it is going

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Speaker 1: you know, from it's starting at a specific point and

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Speaker 1: capturing the entire document as it travels the length of it.

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Speaker 1: And uh, you know, because it's going essentially line by

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Speaker 1: line if you think about that. In pixel tern is

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Speaker 1: taking a row of pixels and then another row of

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Speaker 1: pixels and then you know, as it goes down right. Yeah,

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Speaker 1: I was thinking of it sort of the way television works. Yes,

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Speaker 1: where it'll it'll you have a line by line from

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Speaker 1: the top to the bottom. Um will ignore the interpalation part,

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Speaker 1: otherwise we have to get really complicated. But anyway, the

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Speaker 1: image is painted essentially on your screen from the top

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Speaker 1: to the bottom at a rate that's so fast that

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Speaker 1: your eye does not detect that. It looks like it's

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Speaker 1: all simultaneously projected to you, but it's actually done line

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Speaker 1: by line from the top of the screen to the

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Speaker 1: bottom of the screen. Same thing with a rolling shutter.

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Speaker 1: So when you take a photo or you're using a camcorder.

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Speaker 1: Let's stick with camcorders. So if you're using a camcorder

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Speaker 1: that has a rolling shutter type of image sensors, we're

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Speaker 1: talking cmos. Uh, the the images being recorded from the

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Speaker 1: top to the bottom over and over and over again. Okay,

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Speaker 1: so uh with a cc D camera, it's a global shutter,

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Speaker 1: which means that it's capturing all that data all at once. Yes,

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Speaker 1: sort of like film would. Yeah, so it's not it's

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Speaker 1: not um, you know, it's not something that's gonna be scrolling.

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Speaker 1: It's all one image. So this means that the two

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Speaker 1: different types of image sensors are also prone to two

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Speaker 1: different kinds of flaws that can happen when you're using them. Well,

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Speaker 1: of course, I mean that's that's like any other types

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Speaker 1: of technology. Not everything is suited for every use, right,

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Speaker 1: So let's say that let's i'll talk about the different

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Speaker 1: flaws that you can find. C c D essentially has

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Speaker 1: one type of flaw that you can encounter, which is

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Speaker 1: called the smear effect. So smearing is let's say that

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Speaker 1: you've got a a you're taking an image of something

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Speaker 1: that has a bright light in it. Um Smearing is

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Speaker 1: this effect where you sort of see the light. You'll

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Speaker 1: see like a projection of light above and below it,

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Speaker 1: or you know it's that's that's why it's called smears.

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Speaker 1: It's been extended beyond just a source of light itself.

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Speaker 1: It's kind of like a halo effect, though usually it's

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Speaker 1: more of at least in the samples I've looked at,

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Speaker 1: it's more of a vertical thing where it looks like

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Speaker 1: it's almost like a ray of light that goes straight

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Speaker 1: up and down the the the screen from the source.

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Speaker 1: So that's one of the things that c c D

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Speaker 1: image sensors can fall victim to, but not CMOS. And

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Speaker 1: it's all because that global shutter exposes that image, the

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Speaker 1: whole image simultaneously, and it's all gathering that light. And

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Speaker 1: once the predetermined shutter speed for that global shutter has elapsed,

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Speaker 1: it stops gathering light, turns that that entire exposure into

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Speaker 1: an electronic image, and then starts again. And the rolling

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Speaker 1: shutter just doesn't have that aim effects, so the smear

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Speaker 1: does not happen with that, and it's you know, it's

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Speaker 1: very noticeable. If you see the the effects of this,

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Speaker 1: you'd think, oh, well, that's unfortunate that there's this weird

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Speaker 1: shaft of light right there in the middle of the frame. Well,

402
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Speaker 1: that's that's it for the c c D. Okay, that's

403
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Speaker 1: the that's the one flaw that's c c D image

404
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Speaker 1: sensors can can fall victim to. But they're the one

405
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Speaker 1: known thing that people complain the one thing that people

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Speaker 1: complain about. There are three three different ones for CMOS.

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Speaker 1: The first is called skew Okay, So you've got this

408
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Speaker 1: rolling shutter and it's going from top to bottom as

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Speaker 1: it's recording images. Now, the shutter is going off u

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Speaker 1: multiple times per second. But let's say that you are

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Speaker 1: panning the camera very very quickly from one side to

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Speaker 1: another there, so you're changing the view. Well, you're having

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Speaker 1: a rolling shutter and you're panting the camera. This can

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Speaker 1: cause the idea of skew. So let's say that you

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Speaker 1: have something that's, uh, that's significant, a big thing that's

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Speaker 1: in the frame of the photo, maybe maybe like a tower.

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Speaker 1: All right, so you've got a tower in the frame

418
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Speaker 1: of your image, and you quickly pan from left to right. Well,

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Speaker 1: as you're panning, that shutter is rolling, and if your

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Speaker 1: pan is fast enough, then the shutter is actually going

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Speaker 1: to start building an image where the pixels at the

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Speaker 1: top of the image are further on one side than

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Speaker 1: the pixels that are at the bottom of that image,

424
00:25:39,840 --> 00:25:43,399
Speaker 1: because it's not capturing all that data simultaneously. The outcome

425
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Speaker 1: of that is that you get a skewed image when

426
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Speaker 1: the output image itself is skewed. So that tower, which

427
00:25:50,640 --> 00:25:53,360
Speaker 1: might be perfectly straight when you look at it, when

428
00:25:53,359 --> 00:25:56,320
Speaker 1: you start looking back at the video and you're playing

429
00:25:56,320 --> 00:25:58,879
Speaker 1: it back really slowly, it's only it looks like it's

430
00:25:59,320 --> 00:26:02,280
Speaker 1: leaning or it's diagonal. It's like that. You know, it's

431
00:26:02,320 --> 00:26:05,800
Speaker 1: suddenly not it's not true anymore. Now I understand what's

432
00:26:05,800 --> 00:26:09,440
Speaker 1: wrong with all those vacation pictures I took in pizza. Yeah, exactly,

433
00:26:09,480 --> 00:26:12,760
Speaker 1: that's the that's it. You know, it's no, it's not

434
00:26:12,840 --> 00:26:16,320
Speaker 1: it at all. But anyway, that's that effect is because

435
00:26:16,440 --> 00:26:18,960
Speaker 1: of that rolling shutter, you know. And again, a global

436
00:26:19,000 --> 00:26:21,000
Speaker 1: shutter would not have that problem because it's taking all

437
00:26:21,000 --> 00:26:23,600
Speaker 1: that image, you know, it's taking all the information all

438
00:26:23,640 --> 00:26:26,320
Speaker 1: at once. The rolling shutter is taking it bit by

439
00:26:26,400 --> 00:26:29,000
Speaker 1: you know, line by line. And again it's only if

440
00:26:29,000 --> 00:26:32,439
Speaker 1: you're panning very quickly, because it's this is going so

441
00:26:32,480 --> 00:26:34,880
Speaker 1: many times per second that if you're doing a nice

442
00:26:34,880 --> 00:26:40,280
Speaker 1: slow pan, it's it's not noticeable. Also, you're more likely

443
00:26:40,359 --> 00:26:44,720
Speaker 1: to prevent the kind of nausea that's associated with the

444
00:26:44,720 --> 00:26:47,520
Speaker 1: the quick panning of Yeah, we'll get to there's a

445
00:26:48,160 --> 00:26:53,320
Speaker 1: human advantage to that too. Next is the wobble. Yes,

446
00:26:53,640 --> 00:26:58,440
Speaker 1: so you don't have this problem. No, This is wobble

447
00:26:58,640 --> 00:27:01,439
Speaker 1: is when you get sort of a weird, stretchy or

448
00:27:01,560 --> 00:27:04,520
Speaker 1: rubbery look to stuff that's going on in the video,

449
00:27:05,040 --> 00:27:08,560
Speaker 1: and it tends to happen with handheld footage, right because

450
00:27:08,600 --> 00:27:10,600
Speaker 1: you're when you're holding the camera, you don't have that

451
00:27:10,720 --> 00:27:13,640
Speaker 1: steady base that you would if you're using a tripod.

452
00:27:13,760 --> 00:27:17,560
Speaker 1: So let's say like a found footage film. The sure

453
00:27:17,600 --> 00:27:20,760
Speaker 1: becoming more and more popular these days, so something like

454
00:27:20,800 --> 00:27:24,240
Speaker 1: all Onlines of Blair Witch or clover Field or or

455
00:27:24,280 --> 00:27:29,120
Speaker 1: one of those movies or or or vhs made by

456
00:27:29,200 --> 00:27:34,240
Speaker 1: friends of mine. Check it out. It just it just

457
00:27:34,320 --> 00:27:38,399
Speaker 1: premiered over at Sundance. Um, that's a shout out to

458
00:27:38,440 --> 00:27:41,600
Speaker 1: my buddies anyway, So same sort of thing. It's it's

459
00:27:41,600 --> 00:27:44,359
Speaker 1: because of that rolling shutter, the information is being captured

460
00:27:44,359 --> 00:27:47,600
Speaker 1: line by line. If your camera is not steady then

461
00:27:48,320 --> 00:27:50,160
Speaker 1: and if it's moving around quite a bit and at

462
00:27:50,160 --> 00:27:54,840
Speaker 1: a fairly fast pace, then it's the The images are

463
00:27:54,880 --> 00:27:58,919
Speaker 1: not going to be uh, they're not gonna be clear.

464
00:27:59,160 --> 00:28:02,439
Speaker 1: They're gonna end up having this wobbly, stretchy look. So

465
00:28:02,560 --> 00:28:06,000
Speaker 1: let's say you're panning uh down, so you've got you

466
00:28:06,000 --> 00:28:08,240
Speaker 1: you maybe you've got your looking at the top of

467
00:28:08,280 --> 00:28:12,439
Speaker 1: that tower, and you start panning down very very quickly

468
00:28:12,480 --> 00:28:17,360
Speaker 1: to say, simulate a fall. So we're panting down very

469
00:28:17,440 --> 00:28:21,000
Speaker 1: very quickly. That rolling shutter is going up from the

470
00:28:21,040 --> 00:28:25,480
Speaker 1: top to the bottom very quickly. As you are going down,

471
00:28:25,760 --> 00:28:28,960
Speaker 1: the shutter is going to UH. If you're matching the

472
00:28:28,960 --> 00:28:31,720
Speaker 1: shutter speed or getting close to the shutter speed, it's

473
00:28:31,720 --> 00:28:34,200
Speaker 1: going to make that building stretch out, it's gonna look

474
00:28:34,280 --> 00:28:38,560
Speaker 1: very odd. Um. And so that's another one of those issues.

475
00:28:39,080 --> 00:28:41,880
Speaker 1: And again the global shutter doesn't have that problem because

476
00:28:41,920 --> 00:28:47,080
Speaker 1: it's not it's not capturing information the same way. UH.

477
00:28:47,200 --> 00:28:53,120
Speaker 1: And then finally there's partial exposure. Partial exposure happens when

478
00:28:54,280 --> 00:28:58,080
Speaker 1: light is hitting the shutter or the the image sensor

479
00:28:58,120 --> 00:29:00,880
Speaker 1: at a very particular moment, and and the light is

480
00:29:00,960 --> 00:29:04,360
Speaker 1: hitting it just fast enough so that when the rolling

481
00:29:04,360 --> 00:29:08,160
Speaker 1: shutter starts, the light's not there. But before the rolling

482
00:29:08,160 --> 00:29:12,680
Speaker 1: shutter has finished, it's it's a journey across the image sensor.

483
00:29:13,040 --> 00:29:15,320
Speaker 1: The light has coming gone, which means that part of

484
00:29:15,320 --> 00:29:17,720
Speaker 1: your image is going to be much brighter than the

485
00:29:17,720 --> 00:29:20,520
Speaker 1: rest of your image. So if you think about your

486
00:29:20,520 --> 00:29:23,320
Speaker 1: image as UH, let's say you're taking a picture of,

487
00:29:23,400 --> 00:29:25,920
Speaker 1: say a poster, all right, you gotta you're looking at

488
00:29:25,920 --> 00:29:29,160
Speaker 1: a poster and there's a flash that goes off as

489
00:29:29,200 --> 00:29:31,720
Speaker 1: you are taking your image, and the flash is moving

490
00:29:32,040 --> 00:29:34,040
Speaker 1: at a speed. It's a very quick flash moving. It's

491
00:29:34,080 --> 00:29:38,200
Speaker 1: moving at speed that's faster than the rolling shutter is.

492
00:29:39,440 --> 00:29:41,480
Speaker 1: When you actually look at that picture, when you're looking

493
00:29:41,480 --> 00:29:43,240
Speaker 1: at the poster in the back, it's gonna look like

494
00:29:43,240 --> 00:29:46,479
Speaker 1: there's this one band of the poster that's much more

495
00:29:46,560 --> 00:29:49,600
Speaker 1: brightly lit than the rest of the poster, and that's

496
00:29:49,600 --> 00:29:52,440
Speaker 1: going to be the moment when that flash hit the

497
00:29:52,480 --> 00:29:56,040
Speaker 1: image sensor as the rolling shutter was going down the sensor.

498
00:29:57,640 --> 00:30:00,120
Speaker 1: So this is another issue you have to work with

499
00:30:00,160 --> 00:30:03,880
Speaker 1: your lighting in order to avoid it. And uh, you

500
00:30:03,920 --> 00:30:07,000
Speaker 1: know it can if you're using a flash that's a

501
00:30:07,080 --> 00:30:09,800
Speaker 1: longer based flash, you don't have to worry as much.

502
00:30:10,200 --> 00:30:13,320
Speaker 1: This is why partially why anyway part of it because

503
00:30:13,360 --> 00:30:16,640
Speaker 1: it's most of the the smartphone flashes or l E

504
00:30:16,720 --> 00:30:19,920
Speaker 1: D s, But it's also part of why if you

505
00:30:20,000 --> 00:30:22,480
Speaker 1: ever take a photo with a smartphone that uses an

506
00:30:22,560 --> 00:30:27,120
Speaker 1: LED flash, it tends to last a while. It's because

507
00:30:27,160 --> 00:30:29,160
Speaker 1: if it didn't, then your all your images would come

508
00:30:29,200 --> 00:30:33,040
Speaker 1: out with this weird banding issue. And you don't want

509
00:30:33,080 --> 00:30:36,600
Speaker 1: bands in your in your pictures unless you're at a concert.

510
00:30:37,680 --> 00:30:40,600
Speaker 1: I'll be taking some tonight, awesome, I'm gonna go see

511
00:30:40,640 --> 00:30:44,200
Speaker 1: they might be giants and that's a shoutout today, might

512
00:30:44,200 --> 00:30:48,760
Speaker 1: be giant. Everyone's getting shoutouts today. Apparently it's free plug

513
00:30:48,880 --> 00:30:51,640
Speaker 1: day on tech stuff. Well, you know a lot of

514
00:30:51,640 --> 00:30:54,160
Speaker 1: stuff on tech stuff requires a plug. Yes, it's true.

515
00:30:54,600 --> 00:30:59,480
Speaker 1: Not everything is better reoperated. So yeah, the the c

516
00:30:59,640 --> 00:31:02,880
Speaker 1: c D is only prone to the smear issue, whereas

517
00:31:02,880 --> 00:31:07,120
Speaker 1: CMOS has those other three now have a decent camera

518
00:31:07,200 --> 00:31:09,719
Speaker 1: you shouldn't have, you know, and O are taking precautions.

519
00:31:09,760 --> 00:31:11,960
Speaker 1: You just have to worry about it exactly. Yeah, if

520
00:31:12,040 --> 00:31:13,800
Speaker 1: you if you know what you're doing, you can get

521
00:31:13,840 --> 00:31:16,680
Speaker 1: around these problems. It's just that these are the ones

522
00:31:16,760 --> 00:31:19,520
Speaker 1: that are the cameras are prone to based upon the

523
00:31:19,560 --> 00:31:23,000
Speaker 1: technology they use. So it's not that every single image

524
00:31:23,000 --> 00:31:27,480
Speaker 1: you're gonna take, or even even like a significant percentage

525
00:31:27,480 --> 00:31:31,240
Speaker 1: of the images you'll take will have problems associated with

526
00:31:31,280 --> 00:31:34,080
Speaker 1: these issues that I've talked about, but some of them might.

527
00:31:34,760 --> 00:31:38,360
Speaker 1: And the reason why they they have those is because

528
00:31:38,360 --> 00:31:41,080
Speaker 1: of the technology itself. And again, you know, you just

529
00:31:42,080 --> 00:31:44,720
Speaker 1: little basic tricks that you can do, you know, just

530
00:31:45,120 --> 00:31:48,440
Speaker 1: for example, using a tripod whenever you can helps a lot,

531
00:31:49,320 --> 00:31:51,719
Speaker 1: it'll it'll really remove a lot of this also, you know,

532
00:31:51,800 --> 00:31:55,160
Speaker 1: most of most people aren't running around and jerking the

533
00:31:55,200 --> 00:31:58,360
Speaker 1: camera left and right so fast that these are really

534
00:31:58,520 --> 00:32:03,680
Speaker 1: coming into play. Uh And if you're using Instagram, really,

535
00:32:03,720 --> 00:32:06,160
Speaker 1: you've made your image look so crappy already you don't

536
00:32:06,160 --> 00:32:11,360
Speaker 1: need to worry about these effects. Nice, that's that's just

537
00:32:11,400 --> 00:32:19,360
Speaker 1: a joke. Mostly my wife uses Instagram a lot. What

538
00:32:19,480 --> 00:32:22,480
Speaker 1: a lovely old tiny photo of the Space Shuttle. I'm

539
00:32:22,520 --> 00:32:26,760
Speaker 1: so glad anyway. Uh so, yeah, I mean, so which

540
00:32:27,240 --> 00:32:31,120
Speaker 1: which is better? Really kind of it really does depend

541
00:32:31,160 --> 00:32:34,800
Speaker 1: on what kind of photography you're going to be doing. Um,

542
00:32:34,840 --> 00:32:37,360
Speaker 1: you know, probably the biggest difference is whether you're doing

543
00:32:37,400 --> 00:32:41,160
Speaker 1: still photography or or video. And most of the time

544
00:32:41,160 --> 00:32:44,320
Speaker 1: when you're shopping for cameras, the type of sensor that's

545
00:32:44,360 --> 00:32:47,600
Speaker 1: in it is not necessarily the easiest information for you

546
00:32:47,640 --> 00:32:50,680
Speaker 1: to find out, although it does pay to to look

547
00:32:50,680 --> 00:32:53,000
Speaker 1: into that if you can, and and actually do some

548
00:32:53,040 --> 00:32:56,120
Speaker 1: research on the sensor itself, because like we said, the

549
00:32:56,160 --> 00:32:59,160
Speaker 1: sensor and the lens of the camera is going to

550
00:32:59,200 --> 00:33:01,320
Speaker 1: have a lot more to do with the quality of

551
00:33:01,320 --> 00:33:04,320
Speaker 1: the images that you get using that camera then how

552
00:33:04,320 --> 00:33:07,440
Speaker 1: many megapixels it has. So even if you go out

553
00:33:07,440 --> 00:33:09,400
Speaker 1: there and you buy a twelve megapixel camera and your

554
00:33:09,440 --> 00:33:12,720
Speaker 1: buddy has an eight megapixel camera, your buddy's images maybe

555
00:33:13,320 --> 00:33:16,719
Speaker 1: may look sharper and more vibrant than yours. Again, not

556
00:33:16,840 --> 00:33:19,040
Speaker 1: to do with the megapixels. It's more about the lens

557
00:33:19,080 --> 00:33:22,680
Speaker 1: and the sensory And of course, if you're you're planning

558
00:33:22,680 --> 00:33:25,160
Speaker 1: on dropping a lot of coin on a new camera,

559
00:33:26,040 --> 00:33:28,360
Speaker 1: probably would be a good idea if you read some

560
00:33:28,440 --> 00:33:32,640
Speaker 1: reviews from professionals to give you an idea of what

561
00:33:32,720 --> 00:33:35,040
Speaker 1: to expect and to see if if other people are

562
00:33:35,120 --> 00:33:38,160
Speaker 1: using it the same way, you will be um to

563
00:33:38,280 --> 00:33:40,560
Speaker 1: get to really get an idea of how you know

564
00:33:40,560 --> 00:33:42,720
Speaker 1: whether it's going to suit your needs, and that's the

565
00:33:42,720 --> 00:33:47,320
Speaker 1: most important thing. Very good, yes, good advice from Mr Pallette.

566
00:33:47,680 --> 00:33:49,840
Speaker 1: I think we should probably wrap this up because our

567
00:33:49,880 --> 00:33:53,160
Speaker 1: our guest producer, Liz is out there and she's a

568
00:33:53,200 --> 00:33:56,640
Speaker 1: photographer and she's probably about ready to explode with all

569
00:33:56,680 --> 00:34:00,400
Speaker 1: the information we've given and say, well, actually she hasn't

570
00:34:00,400 --> 00:34:02,720
Speaker 1: screamed it us yet, No I know, but I've seen

571
00:34:02,760 --> 00:34:05,560
Speaker 1: like a couple of things fly at us through the curtains,

572
00:34:05,560 --> 00:34:08,399
Speaker 1: so she's just not Luckily, she throws like a girl,

573
00:34:08,920 --> 00:34:13,399
Speaker 1: so I'm just kidding. I'm just kidding. Actually she could

574
00:34:13,440 --> 00:34:17,360
Speaker 1: probably be me. I'm hearing noises now. I take that back.

575
00:34:18,640 --> 00:34:22,360
Speaker 1: Girls throw really hard, which is harder than I can anyway,

576
00:34:22,640 --> 00:34:25,480
Speaker 1: So let's wrap this up while I shoved my foot

577
00:34:25,520 --> 00:34:28,400
Speaker 1: further into my mouth. If you guys have any comments

578
00:34:28,520 --> 00:34:31,040
Speaker 1: or questions or suggestions for us, you can let us

579
00:34:31,080 --> 00:34:33,719
Speaker 1: know on Facebook or Twitter. Are handled. There is tech

580
00:34:33,760 --> 00:34:36,640
Speaker 1: Stuff h s W or send us an email. Our

581
00:34:36,680 --> 00:34:40,040
Speaker 1: andress is tech Stuff at Discovery dot com and Chris

582
00:34:40,080 --> 00:34:44,600
Speaker 1: and I will talk to you again really soon. Be

583
00:34:44,680 --> 00:34:47,279
Speaker 1: sure to check out our new video podcast, Stuff from

584
00:34:47,320 --> 00:34:50,160
Speaker 1: the Future. Join house Stuff Work staff as we explore

585
00:34:50,200 --> 00:34:54,839
Speaker 1: the most promising and perplexing possibilities of tomorrow. The House

586
00:34:54,840 --> 00:34:57,640
Speaker 1: Stuff Works iPhone app has arrived down at it today

587
00:34:57,880 --> 00:35:04,960
Speaker 1: on iTunes, brought to you by the reinvented two thousand

588
00:35:05,040 --> 00:35:07,080
Speaker 1: twelve camera. It's ready, are you