omplex and high quantization levels are employed, it is impossible to achieve less than 1 bit per pixel, and therefore the efficiency of this system is bounded. At this level of compression for standard broadcast video, 720 X 576, 25 frames/sec, and YUV 4:2:2 color format, a DVD would only be capable of holding just over 30 minutes of video. Clearly a different compression method is required that can achieve higher rates than 1 bit per pixel. Transform Coding As is often the case in engineering, a problem can seem insoluble until it is subjected to a transformation. The widespread deployment of the two-dimensional DCT in image process- ing is such a transform. The image is divided into blocks, typically 8 8, on which the DCT is applied. The transformation is similar to Fourier analysis (Körner, 1988) in that it converts from the time domain into the frequency domain and back again. It should be noted that a block of 8 X 8 pixels in the time domain results in an 8 X 8 block of coefficients in the frequency domain, SO the transformation itself nets no gain; in fact, it could be regarded as an expansion because the frequency domain coefficients are larger than the time domain coefficients. The compression comes from the way in which the coefficients themselves are quantized and owes a lot to the detailed studies done on the spatial frequency responses of the human eye (Pearson, 1975). The graph in Figure 3.7 shows the contrast sensitivity of the human eye. The horizontal axis represents the frequency; the vertical axis, the sensitivity. This graph shows us that the eye has a bandpass characteristic with maximum sensitivity around 8 Hz. The relative insensitivity to frequencies above and below this point can be clearly seen. What the graph shows us is that the human eye is relatively insensitive to high and low spatial frequencies. Note particularly that frequencies beyond 50 cycles per degree are difficult to perceive. With knowledge of human visual response, a codec can be designed to take advantage this phenomenon