![]() (There is a bit overhead for sending this, negligible if the data file is big.) (c) Assign code 0, 1 to the two branches of the tree, and delete the children from OPEN.ĭecoding for the above two algorithms is trivial as long as the coding table (the statistics) is sent before the data. ![]() (b) Assign the sum of the children's frequencies/probabilities to the parent node and insert it into OPEN. (a) From OPEN pick two nodes having the lowest frequencies/probabilities, create a parent node of them. Repeat until the OPEN list has only one node left: Initialization: Put all nodes in an OPEN list, keep it sorted at all times (e.g., ABCDE).Ģ. Recursively divide into two parts, each with approx. ![]() Sort symbols according to their frequencies/probabilities, e.g., ABCDE.Ģ. Q: How about an image in which half of the pixels is white (I = 220) and half is black (I = 10)?Ī simple example will be used to illustrate the algorithm:ġ. pi = 1/256, then the number of bits needed to code each gray level is 8 bits. Indicates the amount of information contained in Si, i.e., the number of bits needed to code Si.įor example, in an image with uniform distribution of gray-level intensity, i.e. Where pi is the probability that symbol Si in S will occur. According to Shannon, the entropy of an information source S is defined as: ![]()
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