Lossless Image Compression Using Super-Spatial Structure Prediction


We recognize that the key challenge in image compression is to efficiently represent and encode high-frequency image structure components, such as edges, patterns, and textures. In this work, we develop an efficient lossless image compression scheme called <i>super-spatial structure prediction</i>. This super-spatial prediction is motivated by motion prediction in video coding, attempting to find an optimal prediction of structure components within previously encoded image regions. We find that this super-spatial prediction is very efficient for image regions with significant structure components. Our extensive experimental results demonstrate that the proposed scheme is very competitive and even outperforms the state-of-the-art lossless image compression methods.

DOI: 10.1109/LSP.2010.2040925

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@article{Zhao2010LosslessIC, title={Lossless Image Compression Using Super-Spatial Structure Prediction}, author={Xiwen Owen Zhao and Zhihai Henry He}, journal={IEEE Signal Processing Letters}, year={2010}, volume={17}, pages={383-386} }