An Evaluation of Arithmetic and Huffman Coding in Data Compression & Source Coding

This paper considers the trouble of records compression and supply coding by evaluating the use of arithmetic and Huffman coding. Arithmetic coding is a good, most reliable coding approach used for statistics compression. It assigns shorter message lengths to symbols that appear extra often in the statistics movement and can reach better compression ratios than maximum different coding strategies. Huffman coding then uses a Tree information shape to manner the source facts and assigns a unique binary code to every symbol within the facts. It is quicker and easier to put in force than arithmetic coding and yields exact average compression ratios. Each coding strategy is compared and discussed in-depth in phrases of compression ratio overall performance, velocity of encode/decode, and complexity. From the assessment and dialogue, it's miles concluded that mathematics coding is a slightly better desire for records compression/supply coding than Huffman coding, with overall higher performance and compression ratio. In contrast, Huffman's coding change into discovered to be quicker and less complicated.