Title :
Low-complexity waveform coding via alphabet and sample-set partitioning
Author :
Said, Amir ; Pearlman, William A.
Author_Institution :
Fac. of Electr. Eng., Univ. Estadual de Campinas, Sao Paulo, Brazil
fDate :
29 Jun-4 Jul 1997
Abstract :
We propose a new low-complexity entropy-coding method to be used for coding waveform signals. It is based on the combination of two schemes: (1) an alphabet partitioning method to reduce the complexity of the entropy-coding process; (2) a new recursive set partitioning entropy-coding process that achieves rates smaller than first order entropy even with fast Huffman adaptive codecs. Numerical results with its application for lossy and loss-less image compression show the efficacy of the new method, comparable to the best known methods
Keywords :
Huffman codes; adaptive codes; channel capacity; codecs; entropy codes; image coding; image sampling; transform coding; waveform analysis; wavelet transforms; Huffman entropy coding; alphabet partitioning method; alphabet-set partitioning; fast Huffman adaptive codecs; first order entropy; lossless image compression; lossy image compression; low-complexity entropy-coding method; low-complexity waveform coding; numerical results; recursive set partitioning entropy-coding; sample-set partitioning; waveform signals coding; wavelet transform coefficients; Arithmetic; Codecs; Entropy; Huffman coding; Image coding; Medical tests; Pixel; Quantization; Testing; Wavelet transforms;
Conference_Titel :
Information Theory. 1997. Proceedings., 1997 IEEE International Symposium on
Conference_Location :
Ulm
Print_ISBN :
0-7803-3956-8
DOI :
10.1109/ISIT.1997.612976
