Bootstrap Analysis of Compression Algorithms
Antonio A. R. Beserra, Leandro Carlos de Souza, Daniel Faustino Lacerda de Souza · IEEE Latin America Transactions · 2020
Compression algorithms have been proposed with the technology advance. However, there are not objective analysis procedures to guide a future choice of an algorithm directed for the type of data in the system they are intended for. This paper introduces a statistical framework, based on the bootstrap method, to execute the analysis of compression algorithms using an objective comparison parameter as a criterion. A case study using the compression ratio as the parameter and file samples of 4 different types was analyzed. The proposed scheme allowed us to infer which algorithm is better to be used for each data type. RLE has proven more suitable to image, audio and video files with Huffman obtaining comparable performance. For text files, LZW has remarkably outperformed all other algorithms.