Context-based lossless image compression with optimal codes for discretized Laplacian distributions

Ciprian Doru Giurcaneanu; Ioan Tabus; Cosmin Stanciu

doi:10.1117/12.481916

28 May 2003 Context-based lossless image compression with optimal codes for discretized Laplacian distributions

Ciprian Doru Giurcaneanu, Ioan Tabus, Cosmin Stanciu

Proceedings Volume 5014, Image Processing: Algorithms and Systems II; (2003) https://doi.org/10.1117/12.481916
Event: Electronic Imaging 2003, 2003, Santa Clara, CA, United States

Abstract

Lossless image compression has become an important research topic, especially in relation with the JPEG-LS standard. Recently, the techniques known for designing optimal codes for sources with infinite alphabets have been applied for the quantized Laplacian sources which have probability mass functions with two geometrically decaying tails. Due to the simple parametric model of the source distribution the Huffman iterations are possible to be carried out analytically, using the concept of reduced source, and the final codes are obtained as a sequence of very simple arithmetic operations, avoiding the need to store coding tables. We propose the use of these (optimal) codes in conjunction with context-based prediction, for noiseless compression of images. To reduce further the average code length, we design Escape sequences to be employed when the estimation of the distribution parameter is unreliable. Results on standard test files show improvements in compression ratio when comparing with JPEG-LS.

Citation Download Citation

Ciprian Doru Giurcaneanu, Ioan Tabus, and Cosmin Stanciu "Context-based lossless image compression with optimal codes for discretized Laplacian distributions", Proc. SPIE 5014, Image Processing: Algorithms and Systems II, (28 May 2003); https://doi.org/10.1117/12.481916

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