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Comparison of image compression techniques using Huffman and Lempel-Ziv-Welch algorithms
- 1 Glasgow College, University of Electronic Science and Technology of China, Chengdu, Sichuan, 611731, China
* Author to whom correspondence should be addressed.
Abstract
Image compression technology is very popular in the field of image analysis because the compressed image is convenient for storage and transmission. In this paper, the Huffman algorithm and Lempel-Ziv-Welch (LZW) algorithm are introduced. They are widely used in the field of image compression, and the compressed image results of the two algorithms are calculated and compared. Based on the four dimensions of Compression Ratio (CR), Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR) and Bits Per Pixel (BPP), the applicable conditions of the two algorithms in compressing small image files are analysed. The results illustrated that when the source image files are less than 300kb, the Compression Ratio (CR) of Huffman algorithm was better than that of LZW algorithm. However, for Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR) and Bits Per Pixel (BPP), which are used to represent the compressed images qualities, LZW algorithm gave more satisfactory results.
Keywords
Huffman, Lempel-Ziv-Welch, image compression
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Cite this article
Ma,S. (2023). Comparison of image compression techniques using Huffman and Lempel-Ziv-Welch algorithms. Applied and Computational Engineering,5,793-801.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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Volume title: Proceedings of the 3rd International Conference on Signal Processing and Machine Learning
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