COMPARATIVE ANALYSIS AND PERFORMANCE EVALUATION OF HUFFMAN AND SHANNON FANO DATA COMPRESSION ALGORITHMS USING THE REDUCTION OF STORAGE SIZE OF A GIVEN DATA STRING.
DOI:
https://doi.org/10.60787/jnamp-v67i1-337Keywords:
Deduplication, Algorithm, Compression, Data encoding, Average code lengthAbstract
Even with bigger storage disks, it is very necessary to explore opportunities to maximize the potential capacity of the required storage disks. The act of transforming data such that it uses less memory space is known as data compression. Huffman and Shannon Fano encoding algorithms can compress different forms of data such as images, text, audio, and video. This paper centres on a comparative evaluation of the stated data encoding algorithms in terms of code word generation operations, average code length per symbol, CRP, compression factor, and time complexity analysis with a sample data string. The evaluation culminated in the computation and a pictorial representation of the running time of the two data encoding algorithms. The Huffman encoding algorithm takes a shorter time than Shannon Fano encoding algorithm. However, the two compressions have similar average code length per symbol and operate within the same compression ratio and factor performance
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