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