tropy coding method can then produce an efficient coded message. If one can calculate the probability that a pixel takes a particular colour, then an effi- cient coded message can be produced. As can be observed from Figure 5.18, the probability that a pixel takes a particular colour is highly correlated with its neighbouring pixel's colour. For example, a grey pixel is highly likely to be next to another similar grey coloured pixel. One way to decorrelate the image is by calculating the difference between neighbouring pixels. We can start from the top-left pixel, note the colour and assign a specific code. The next pixel has a slightly different colour, the difference can be measured and a code assigned. One can move across horizontal and vertical axes and measure the difference in pixel colours, assign a code to the difference and compile them into a file which represents the image information. Such an encoding method can be significantly more efficient than when pixel correlation is not considered. The encoded image size can be further reduced if an entropy coding technique, such as Huffman coding, is used to encode the inter-pixel difference values. This is the principle behind the image coding Portable Network Graphic (.png file format) method for lossless image compression. PNG compression is useful for images where pixel- to-pixel variation is small or zero, such as text or graphic images, for example for computer screen dumps as shown in Figure 5.19. horizontal and vertical axes and measure the difference in pixel colours, assign a code to the difference and compile them into a file which represents the image information. Such an encoding method can be significantly more efficient than when pixel correlation is not considered. The encoded image size can be further reduced if an entropy coding technique, such as Huffman coding is used to encode the inter-pixel difference values. This is the principle behind image coding Portable Network Graphic (.png file format) method for lossless image compression. PNG 