Appendix 1

Appendix 1: Understanding the NTSC Video Format and Digital Video
Let’s look at a simplifi ed example. Let’s say we have 4 pixels in our interval. The values of the pixels
are 2, 4, 7, and 5. So the fi rst checksum is 18. Now the values are multiplied by their position. They
become 2, 8, 21, and 20. The second checksum is therefore 51. Now let’s say in playback we get
values of 2, 6, 7, and 5. This checksum is 20, so we know something is over by 2. But which value
is over? The second checksum is 55, or 4 over. Four is twice 2 so we know the second value is the
errant pixel and it is repaired.
Another system uses interleaving and interpolation. In interleaving, the pixels are not recorded in
order, but are recorded in a predictable pattern. The fi rst pixel may be the fi ftieth recorded, the second
pixel may be the third recorded, the third may be the thirty-second value recorded. Now, if there is
damage on the tape and twelve values in a row are dropped out, the missing information is scattered
all over the image. If several values in the checksum interval have been lost, there is no hope of the
checksum error correction fi xing the problem. However, because the missing pixels are scattered all
over the image, the pixels surrounding the missing pixel can be averaged and this value used in place
of the missing pixel.
While good, this process cannot re-create the exact data. This creates undesirable artifacts and loss
of image quality. All recordings have some dropout, DV recordings on poor tape have a lot more
dropouts than DVCam or DVC Pro recordings on high-quality tape. Good tape and strong signal
does make a difference.
In spite of the fact that videotape is the most common system for recording digital video, it is slowly
becoming obsolete. At some point all video will likely be shot on hard drive, optical disc, or memory
chips.
Compression
Any digital video signal that is being recorded or transmitted will be compressed. The amount of
data needs to be brought down to a manageable bandwidth. Some formats claim to be “uncompressed,”
but this is not exactly true. They may be “lossless,” in other words, all the compressed
information is recovered intact in playback, but anyone would want to record as much data as possible.
All formats use some compression, it would be foolish not to.
Here’s an analog for lossless compression: Let’s say you are a sheepherder and for some strange
reason you want to count the sheep’s feet. Look, it’s just an analog, go with it for a minute. So rather
than count the feet, it makes more sense to count the sheep and multiply by four. Unless one of the
sheep has a really bad limp, you can assume this is 100 percent accurate, totally lossless compression
of the data. But now let’s say you don’t want to count all those sheep every time. You need to know
how many feet there are out there, so you dip one of every ten sheep in blue die. Now you can count
the blue sheep, multiply by forty and that’s how many feet they have. This is also more or less
accurate, unless of course one of the sheep wanders off and gets eaten by a wolf. And if the herd
can’t be divided into tens, you will need to round the number off. So some of your data is now
potentially lost using this “lossy” compression scheme.
We can do something similar with video compression. In this case, we need to know the color value
of all of our pixels, but we don’t want to record all of these values. The fi rst thing we can do is look at
all of the pixels around one pixel. If the fi rst four pixels in a video line are all more or less the same
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