DocumentCode
2685061
Title
Adaptive linear prediction lossless image coding
Author
Motta, Giovanni ; Storer, James A. ; Carpentieri, Bruno
Author_Institution
Dept. of Comput. Sci., Brandeis Univ., Waltham, MA, USA
fYear
1999
fDate
29-31 Mar 1999
Firstpage
491
Lastpage
500
Abstract
The practical lossless digital image compressors that achieve the best results in terms of compression ratio are also simple and fast algorithms with low complexity both in terms of memory usage and running time. Surprisingly, the compression ratio achieved by these systems cannot be substantially improved even by using image-by-image optimization techniques or more sophisticate and complex algorithms. Meyer and Tischer (1998) were able, with their TMW, to improve some current best results (they do not report results for all test images) by using global optimization techniques and multiple blended linear predictors. Our investigation is directed to determine the effectiveness of an algorithm that uses multiple adaptive linear predictors, locally optimized on a pixel-by-pixel basis. The results we obtained on a test set of nine standard images are encouraging, where we improve over CALIC on some images
Keywords
adaptive codes; computational complexity; data compression; image coding; linear predictive coding; optimisation; complexity; compression ratio; digital image compressors; local optimization; lossless image coding; multiple adaptive linear prediction; Compressors; Computational complexity; Digital images; Entropy; IEC standards; ISO; Image coding; Performance loss; Pixel; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Data Compression Conference, 1999. Proceedings. DCC '99
Conference_Location
Snowbird, UT
ISSN
1068-0314
Print_ISBN
0-7695-0096-X
Type
conf
DOI
10.1109/DCC.1999.755699
Filename
755699
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