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OT : Video Capture question


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I got myself a video capture card, and am converting some old home tapes to DVD. My question is: what is the difference between RGB24, YUY2, and UYVY? And which should I use, and why?


I've been poking around the internet, and the answers I've found were entirely too technical to understand, or have been 3 word answers which don't explain anything to me.



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Hey PaulyWally. I write drivers and software for capture boards, frame grabbers and digital cameras.


I'm not sure what kind of answer you're looking for so the simple answer is:


The difference between those classes are the pixel orders and you should be using RGB-24.


So, here is the long answer(s) if you are interested...


The digitization process divides an image into a horizontal grid, or array, of very small regions called "picture elements," or "pixels".


In the computer, the image is represented by this digital grid, or bitmap. Each pixel in the bitmap is identified by its position in the grid, as referenced by its row (x) and column (y) number. By convention, pixels are referenced from the upper-left position of the bitmap, which is considered position 0,0 (row 0, column 0).


When a source image, such as a photograph, is digitized, it is examined in grid fashion. That is, each pixel in the image is individually sampled, and its brightness is measured and quantified. This measurement results in a value for the pixel, usually an integer, which represents the brightness or darkness of the image at that point. This value is stored in the corresponding pixel of the computer's image bitmap.


When the image is digitized, the width and height of the array are chosen and fixed. This is dictated by the model(s) you mentioned earlier. Together, the bitmap's pixel width and height are known as its spatial resolution.


Depending upon the capability of the measuring hardware and the complexity of the image, anywhere from 1 to 32 bits might be used to store each pixel value.


Pixel values for line art images, which contain only black and white information, can be easily represented by a single bit: 0=black, 1=white.


However, a photographic-like image contains much more information...it takes 24 bits to represent all the possible colors that might occur in a true color image. Given 24 bits, over 16 million colors, far more than the human eye can differentiate, can be represented.


The number of bits used to represent the pixel values in an image is referred to as its pixel depth, or bits-per-pixel (BPP). The number of bits per pixel used to represent each pixel value determines the image's class.


A color model is simply a standard way to represent color in mathematical terms. Most color models use a 3D-coordinate system. Each point within the system's subspace represents a unique color. The RGB color model, for example, can be visualized as a cube where Red is the X-axis, Blue is the Y-axis and Green is the Z-axis. Each one of the 16.8 million colors is described by a unique point within this cube.


There are many color models in use today: the RGB color model (Red, Green, Blue), HSI color model (Hue, Saturation, Intensity) and HSV color model (Hue, Saturation, Value) models are most frequently used in digital image processing. The CMY (Cyan, Magenta, Yellow) model is a standard used to describe color in the color printing industry, and YIQ color model(Y-axis, In-phase, Quadrature) is used in broadcast television.


RGB color model

The RGB (Red, Green, Blue) color model is an especially important one in digital image processing because it is used by most digital imaging devices (e.g., monitors and color cameras). In the RGB model, a color is expressed in terms that define the amounts of Red, Green and Blue light it contains.


In a 24-bit, color image, pure red would be represented as 255/000/000, where 255 represents the highest level of red light possible, untainted by any green (000) or blue (000) light. Various combinations of the Red, Green and Blue values allow us to define 224 (over 16 million) colors.


I could go on and on, most of this comes from documentation i've written for our software.


But, again, you should be using RGB-24 as it is the most understood format and should not require a codec.


hope this helps

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Hmmm... still pretty technical, but more easily understood. :)


Based on what you wrote (and other things I've read), would this statement be accurate:


YUV (and it's derivatives) may have been the "safer" choice up until several years ago because it is natively anolog. But now that home video has pretty much exclusively moved into digital, RGB24 will give the best quality and richest color depth on any video monitor/TV.


At least... that's how I'm understanding it at this point.


Thanks again!

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In the context if this conversation, yes.


In the imaging industry at large, no. All color models and signal types have unique aspects that lend themselves to particular applications.


I deal specifically with Scientific Image Acquisition and Analysis. Some applications aren't at all concerned with Qualitative information (how it looks to you and me). For example, some military and scientific applications look only at certain spectrums of light and the RGB color model is virtually useless. Other applications deal with reactions that occur outside of visible spectrums and/or over just a few nanoseconds. In these cases, we ignore color models all together and deal only with theoretical interpolation of data.


Ok, enough geeking out...


If your goal is to capture analog videos (VHS) into a digital environment (computer), your best class is going to be RGB 24.

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