Multi-Description Image Compression Coding Algorithm Based on Depth Learning


Yong Zhang, Guoteng Hui, Lei Zhang, Journal of Information Processing Systems Vol. 19, No. 2, pp. 232-239, Apr. 2023  

https://doi.org/10.3745/JIPS.02.0193
Keywords: Compressed sensing, Deep Learning, ICC Algorithm, Multi-Description Image Coding
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Abstract

Aiming at the poor compression quality of traditional image compression coding (ICC) algorithm, a multidescription ICC algorithm based on depth learning is put forward in this study. In this study, first an image compression algorithm was designed based on multi-description coding theory. Image compression samples were collected, and the measurement matrix was calculated. Then, it processed the multi-description ICC sample set by using the convolutional self-coding neural system in depth learning. Compressing the wavelet coefficients after coding and synthesizing the multi-description image band sparse matrix obtained the multidescription ICC sequence. Averaging the multi-description image coding data in accordance with the effective single point’s position could finally realize the compression coding of multi-description images. According to experimental results, the designed algorithm consumes less time for image compression, and exhibits better image compression quality and better image reconstruction effect.


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Cite this article
[APA Style]
Zhang, Y., Hui, G., & Zhang, L. (2023). Multi-Description Image Compression Coding Algorithm Based on Depth Learning. Journal of Information Processing Systems, 19(2), 232-239. DOI: 10.3745/JIPS.02.0193.

[IEEE Style]
Y. Zhang, G. Hui, L. Zhang, "Multi-Description Image Compression Coding Algorithm Based on Depth Learning," Journal of Information Processing Systems, vol. 19, no. 2, pp. 232-239, 2023. DOI: 10.3745/JIPS.02.0193.

[ACM Style]
Yong Zhang, Guoteng Hui, and Lei Zhang. 2023. Multi-Description Image Compression Coding Algorithm Based on Depth Learning. Journal of Information Processing Systems, 19, 2, (2023), 232-239. DOI: 10.3745/JIPS.02.0193.