1 October 2006 Lossless image compression via bit-plane separation and multilayer context tree modeling
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Color separation and highly optimized context tree modeling for binary layers have provided the best compression results for color map images that consist of highly complex spatial structures but only a relatively few number of colors. We explore whether this kind of approach works on photographic and palette images as well. The main difficulty is that these images can have a much higher number of colors, and it is therefore much more difficult to exploit spatial dependencies via binary layers. The original contributions of this work include: 1. the application of context-tree-based compression (previously designed for map images) to natural and color palette images; 2. the consideration of four different methods for bit-plane separation; and 3. Extension of the two-layer context to a multilayer context for better utilization of the crosslayer correlations. The proposed combination is extensively compared to state of the art lossless image compression methods.
© (2006) Society of Photo-Optical Instrumentation Engineers (SPIE)
Alexey Podlasov, Alexey Podlasov, Pasi Franti, Pasi Franti, } "Lossless image compression via bit-plane separation and multilayer context tree modeling," Journal of Electronic Imaging 15(4), 043009 (1 October 2006). https://doi.org/10.1117/1.2388255 . Submission:

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