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An improved lossless image compression algorithm based on Huffman coding

  • 1193: Intelligent Processing of Multimedia Signals
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Abstract

There is an increasing number of image data produced in our life nowadays, which creates a big challenge to store and transmit them. For some fields requiring high fidelity, the lossless image compression becomes significant, because it can reduce the size of image data without quality loss. To solve the difficulty in improving the lossless image compression ratio, we propose an improved lossless image compression algorithm that theoretically provides an approximately quadruple compression combining the linear prediction, integer wavelet transform (IWT) with output coefficients processing and Huffman coding. A new hybrid transform exploiting a new prediction template and a coefficient processing of IWT is the main contribution of this algorithm. The experimental results on three different image sets show that the proposed algorithm outperforms state-of-the-art algorithms. The compression ratios are improved by at least 6.22% up to 72.36%. Our algorithm is more suitable to compress images with complex texture and higher resolution at an acceptable compression speed.

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Acknowledgments

This work was supported in part by the National Natural Science Foundation of China, under Grants 62020106011, 62071287, and 62001279.

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This work was supported in part by the National Natural Science Foundation of China, under Grants 62020106011, 62071287, and 62001279.

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  1. Shanghai Institute for Advanced Communication and Data Science, School of Communication and Information Engineering, Shanghai University, Shanghai, 200444, China

    Xiaoxiao Liu, Ping An, Yilei Chen & Xinpeng Huang

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  1. Xiaoxiao Liu
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  2. Ping An
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  3. Yilei Chen
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  4. Xinpeng Huang
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Liu, X., An, P., Chen, Y. et al. An improved lossless image compression algorithm based on Huffman coding. Multimed Tools Appl 81, 4781–4795 (2022). https://doi.org/10.1007/s11042-021-11017-5

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