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Lossless Image Compression Using Super-Spatial Structure Prediction

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2 Author(s)
Zhao, X.O. ; Dept. of Electr. & Comput. Eng., Univ. of Missouri, Columbia, MO, USA ; He, Z.H.

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 super-spatial structure prediction. 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.

Published in:

Signal Processing Letters, IEEE  (Volume:17 ,  Issue: 4 )