Title :
LOCO-I: a low complexity, context-based, lossless image compression algorithm
Author :
Weinberger, Marcelo J. ; Seroussi, Gadiel ; Sapiro, Guillermo
Author_Institution :
Hewlett-Packard Co., Palo Alto, CA, USA
Abstract :
LOCO-I (low complexity lossless compression for images) is a novel lossless compression algorithm for continuous-tone images which combines the simplicity of Huffman coding with the compression potential of context models, thus “enjoying the best of both worlds.” The algorithm is based on a simple fixed context model, which approaches the capability of the more complex universal context modeling techniques for capturing high-order dependencies. The model is tuned for efficient performance in conjunction with a collection of (context-conditioned) Huffman codes, which is realized with an adaptive, symbol-wise, Golomb-Rice code. LOCO-I attains, in one pass, and without recourse to the higher complexity arithmetic coders, compression ratios similar or superior to those obtained with state-of-the-art schemes based on arithmetic coding. In fact, LOCO-I is being considered by the ISO committee as a replacement for the current lossless standard in low-complexity applications
Keywords :
Huffman codes; adaptive codes; computational complexity; data compression; image coding; Huffman coding; LOCO-I; adaptive symbol-wise Golomb-Rice code; compression ratios; context models; continuous-tone images; fixed context model; high-order dependencies; low complexity context-based lossless image compression algorithm; low complexity lossless compression for images; Arithmetic; Context modeling; Costs; Decoding; Entropy; Image coding; Laboratories; Pixel; Predictive models; Probability distribution;
Conference_Titel :
Data Compression Conference, 1996. DCC '96. Proceedings
Conference_Location :
Snowbird, UT
Print_ISBN :
0-8186-7358-3
DOI :
10.1109/DCC.1996.488319