Abstract
In this paper, we propose a very simple and efficient binary run-length compression technique for non-binary sources. The technique is based on mapping the non-binary information source into an equivalent binary source using a new fixed-length code instead of the ASCII code. The codes are chosen such that the probability of one of the two binary symbols; say zero, at the output of the mapper is made as small as possible. Moreover, the “all ones” code is excluded from the code assignments table to ensure the presence of at least one “zero” in each of the output codewords. Compression is achieved by encoding the number of “ones” between two consecutive “zeros” using either a fixed-length code or a variable-length code. When applying this simple encoding technique to English text files, we achieve a compression of 5.44bits/character and 4.6bits/character for the fixed-length code and the variablelength (Huffman) code, respectively.
Highlights
The main objective of researchers working in the field of data compression is to design simple and efficient data compression algorithms
When studying the statistics of the binary data at the output of the counter, It is found that the probability distribution of the number of "ones" between two "zeros" (NOBTZ) is non-uniform
Our objective is to look for the optimum mapping process, which gives the minimum entropy for the NOBTZ source to achieve more compression efficiency
Summary
The main objective of researchers working in the field of data compression is to design simple and efficient data compression algorithms. Information sources with small number of alphabet such as black-and-white images has very simple source encoding techniques and they are very suitable for hardware implementation. For such small alphabet sources, run-length encoders are found to be efficient and very simple to be implemented in hardware [4]. Run-length encoding can be applied to any information source provided that it contains large number of sequences of consecutive identical symbols in order to achieve good data compression. Applying the binary run-length encoder to the resulting binary source is found to be very effective both in implementation simplicity and in compression efficiency.
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