Lossless Audio Compression using DWT, DCT and Huffman-based LZW Encoding

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 combinat...

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Bibliographic Details
Main Authors: Abu, Sean Kenneth, Jorquia, Josh Rael, Mendoza, Jose Marie, Tolentino, Carl Timothy, Lucas, Crisron Rudolf
Format: Conference Proceeding
Language:English
Subjects:
audio data compression
Discrete wavelet transforms
Encoding
Entropy
entropy encoding
Information and communication technology
Multimedia systems
PSNR
Transforms
wavelet transform
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Summary: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) (\sim78%), 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.
ISSN:2643-6175
DOI:10.1109/ISCIT57293.2023.10376073