DocumentCode :
2663478
Title :
Improving fractal image compression schemes through quantization and entropy coding
Author :
Ghazel, M. ; Khandani, A.K. ; Vrscay, E.R.
Author_Institution :
Dept. of Electr. & Comput. Eng., Waterloo Univ., Ont., Canada
Volume :
2
fYear :
1998
fDate :
24-28 May 1998
Firstpage :
661
Abstract :
We explore the transform coefficients of various fractal-based schemes for statistical dependence and exploit correlations to improve the compression capabilities of these schemes. In most of the standard fractal-based schemes, the transform coefficients exhibit a degree of linear dependence that can be exploited by using an appropriate vector quantizer such as the LBG algorithm. Additional compression is achieved by lossless Huffman coding of the quantized coefficients
Keywords :
Huffman codes; entropy codes; fractals; image coding; statistical analysis; transforms; vector quantisation; LBG algorithm; correlations; entropy coding; fractal image compression schemes; linear dependence; lossless Huffman coding; quantization; quantized coefficients; statistical dependence; transform coefficients; vector quantizer; Entropy coding; Fractals; Huffman coding; Image coding; Image resolution; Image storage; Inverse problems; Mathematics; Transform coding; Vector quantization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical and Computer Engineering, 1998. IEEE Canadian Conference on
Conference_Location :
Waterloo, Ont.
ISSN :
0840-7789
Print_ISBN :
0-7803-4314-X
Type :
conf
DOI :
10.1109/CCECE.1998.685583
Filename :
685583
Link To Document :
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