@incollection{furht_huffman_2008,
	title = {Huffman {Coding}},
	copyright = {©2008 Springer-Verlag},
	isbn = {978-0-387-74724-8 978-0-387-78414-4},
	url = {http://link.springer.com/referenceworkentry/10.1007/978-0-387-78414-4_338},
	abstract = {The most popular entropy-based encoding technique is the Huffman code [1]. It provides the least amount of information units (bits) per source symbol. This short article describes how it works.The first step in the Huffman algorithm consists in creating a series of source reductions, by sorting the probabilities of each symbol and combining the (two) least probable symbols into a single symbol, which will then be used in the next source reduction stage. Figure 1 shows an example of consecutive source reductions. The original source symbols appear on the left-hand side, sorted in decreasing order by their probability of occurrence. In the first reduction, the two least probable symbols (a3 with prob. = 0.06 and a5 with prob. = 0.04) are combined into a composite symbol, whose probability is 0.06 + 0.04 = 0.1. This composite symbol and its probability are copied onto the first source reduction column at the proper slot (so as to enforce the requirement that the probabilities are sorted i ...},
	language = {en},
	urldate = {2016-05-03},
	booktitle = {Encyclopedia of {Multimedia}},
	publisher = {Springer US},
	editor = {Furht, Borko},
	year = {2008},
	note = {00000},
	pages = {288--289}
}

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