ITCROct 3, 2021

Binary code optimization

arXiv:2110.00917v11 citations
Originality Synthesis-oriented
AI Analysis

This addresses data storage and transmission efficiency for binary data users, but it appears incremental as it builds on existing Huffman coding techniques.

The paper tackles binary data compression by proposing a method to replace original codewords with Huffman codewords, ensuring positive compression for any binary data type, with results showing the compressed data size is always less than or equal to the original.

This article shows that any type of binary data can be defined as a collection from codewords of variable length. This feature helps us to define an Injective and surjective function from the suggested codewords to the required codewords. Therefore, by replacing the new codewords, the binary data becomes another binary data regarding the intended goals. One of these goals is to reduce data size. It means that instead of the original codewords of each binary data, it replaced the Huffman codewords to reduce the data size. One of the features of this method is the result of positive compression for any type of binary data, that is, regardless of the size of the code table, the difference between the original data size and the data size after compression will be greater than or equal to zero. Another important and practical feature of this method is the use of symmetric codewords instead of the suggested codewords in order to create symmetry, reversibility and error resistance properties with two-way decoding.

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