to white transitions: it has relatively less information and can be source coded with relatively fewer bits. Figure 5.22(b) has many more transitions and is encoded using a larger file. A lossy encoder can remove some of these high frequency components without significantly reducing the perceptual quality of image reproduction. The images to the right are the DCT produced images in the frequency domain. As expected, Figure 5.22(c) has less high frequency information, and the white dots are concentrated in the top left part of the image. Figure 5.22(d) shows more high frequency throughout the DCT result [25]. The frequency domain representation facilitates a lossy compression of an image. For example the image may have small significant high frequency transitions, which are those shown in the lower-right corner of Figure 5.21. These may be discarded with little loss of per- ceptual quality. Progressively more and more of the high frequency components may be deleted, resulting in smaller size files but with lower quality. An example of an image with three levels of compression is shown in Figure 5.23. As it can be seen, the sharpness of edges is lost as more and more high frequency transitions are removed. Figure 5.20 An 8x8 pixel grey-scale image. Source: https://commons.wikimedia.org/wiki/File: Letter-a-8x8.png Figure 5.21 The set of possible 8 pixel grey-scale transitions. Source: https://commons.wikimedia. org/wiki/File:DCT-8x8.png Figure 5.22 Two images with different amounts of grey-scale transitions. Source: Ref. [25] From Analogue to Digital Figure 5.23 Three compression levels, with file sizes (from left to right) of 83.2, 9.5 and 4.8 kilobytes. Source: Ref. [26] Video Coding As video signals are simply a sequence of images, video coding uses image coding tech- niques such as described above. Video coding also takes advantage of temporal similarities between consecutive image frames to reduce the number of bits required to encode moving images. A to D conversion of video while possible is impractical. Broa