 standard developed? What are the main reasons for the slow popular uptake of MP3 devices? Why could Apple popularise MP3? How was the network-mediated platform concept applicable? How has the iTunes platform expanded? How is Apple a player in the content and services layer of the broadband ecosystem? Image Coding A digital image consists of pixels of different colours (Figure 5.18). As discussed in Chapter 4, the number of possible colours a pixel may take determines how many bits are required to rep- resent a pixel. For example if 256 possible colours exist then 8 bits (28 = 256) are required to represent one pixel. If such an image has dimensions of 40x40 pixels, then the total number of bits required to represent this image is 40 * 40 * 8 = 12 2 800 bits. Such a coding technique is used for example in uncompressed bitmap (resulting in files with .bmp extension). Figure 5.18 Pixels making up an image Broadband Telecommunications Technologies and Management Pixel-based coding is not very efficient as it does not take the correlation between neigh- bouring pixels' colours into account. Furthermore, it does not take the perceptual content of the image into account. For example, the human visual system is insensitive to rapid pixel colour transitions and therefore insignificant perceptual information may be discarded with little or no visual impact. While such a technique leads to loss of some information, the perceptual clarity of the image can be closely reproduced. Based on this principle, a number of image coding techniques have been developed to facilitate both lossless and lossy compression, thereby resulting in a significantly reduced number of bits required to represent an image. Lossless Image Coding Lossless image coding is possible if correlation between adjacent pixels is taken into consideration. Information theory teaches that the total information content of an image can be calculated by the probability that an individual pixel takes a particular colour, summed over the total number of pixels. An en