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arXiv:2004.02872eess.IV

Lossless Image Compression through Super-Resolution

Sheng Cao, Chao-Yuan Wu, Philipp Krähenbühl

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Abstract

We introduce a simple and efficient lossless image compression algorithm. We store a low resolution version of an image as raw pixels, followed by several iterations of lossless super-resolution. For lossless super-resolution, we predict the probability of a high-resolution image, conditioned on the low-resolution input, and use entropy coding to compress this super-resolution operator. Super-Resolution based Compression (SReC) is able to achieve state-of-the-art compression rates with practical runtimes on large datasets. Code is available online at https://github.com/caoscott/SReC.

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Subjects
eess.IVImage and Video Processing cs.CVComputer Vision and Pattern Recognition cs.LGMachine Learning

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  1. Lossless Image Compression Through Super-Resolution 1 comment

    • First author here. First of all thanks so much for the interest in SReC! It was a pleasant surprise seeing my research on top of Hacker News. Answering a few questions from reading the comments: How is this lossless? The entropy coder is what makes this technique lossless. The…

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