Video Compression-Students Report

Of all the different sources of data, perhaps the one that produces the largest amount of data is
video. Consider a video sequence generated using the CCIR 601 format (Section 19.4). Each
image frame is made up of more than a quarter million pixels. At the rate of 30 frames per
second and 16 bits per pixel, this corresponds to a data rate of about 21 Mbytes or 168 Mbits
per second. This is certainly a change from the data rates of 2.4, 4.8, and 16 kbits per second
that are the targets for speech coding systems discussed in Chapter 18.
Video compression can be viewed as the compression of a sequence of images; in other
words, image compression with a temporal component. This is essentially the approach we will
take in this chapter. However, there are limitations to this approach. We do not perceive motion
video in the same manner as we perceive still images. Motion video may mask coding artifacts that would be visible in still images. On the other hand, artifacts that may not be visible in
reconstructed still images can be very annoying in reconstructed motion video sequences. For
example, consider a compression scheme that introduces a modest random amount of change
in the average intensity of the pixels in the image. Unless a reconstructed still image was being
compared side by side with the original image, this artifact may go totally unnoticed. However,
in a motion video sequence, especially one with low activity, random intensity changes can
be quite annoying. As another example, poor reproduction of edges can be a serious problem
in the compression of still images. However, if there is some temporal activity in the video
sequence, errors in the reconstruction of edges may go unnoticed.