Lossless Audio Compression using DWT, DCT and Huffman-based LZW Encoding
Sean Kenneth Abu, Josh Rael Jorquia, Jose Marie Mendoza, Carl Timothy Tolentino, Crisron Rudolf Lucas · 2023
As digital content and multimedia files increase in quality and size, there is a growing need for audio signal compression to aid in a more efficient signal transmission, network systems management, and processing of data. In this study, a lossless compression method was implemented using a combination of Discrete Wavelet Transform (DWT) and Discrete Cosine Transform (DCT) [1] [2] to decompose audio signals. Furthermore, Huffman-based Lempel-Ziv-Welch (LZW) coding algorithm [3] was used for the entropy encoding. The resulting compressed files were stored in MATLAB raw files to produce an average of 4.4 compression ratio(CR) ($\sim$78%), a peak signal-to-noise ratio(PSNR) of 62dB across a small audio sample and an average of 1.63 CR and 39.51dB PSNR on GTZAN music/speech dataset.