DocumentCode :
2651186
Title :
Multiple non-orthogonal bases representations for images
Author :
Ragothaman, Pradeep ; Mikhael, Wasfy B.
Author_Institution :
Dept. of Electr. & Comput. Eng., Central Florida Univ., Orlando, FL, USA
Volume :
2
fYear :
2004
fDate :
7-10 Nov. 2004
Firstpage :
1545
Abstract :
Conventional image compression techniques usually involve use of a single transform in conjunction with other techniques like vector quantization etc. In this paper, the concept of using more than one transform, i.e., using multiple non-orthogonal bases functions representation, for still image compression, is presented. Sample results show that this approach used in conjunction with an efficient vector quantization technique - an adaptive energy based split vector quantization technique, gives improved reconstruction quality of images for the same bit rate compared to existing single transform methods.
Keywords :
image coding; image representation; transforms; vector quantisation; adaptive energy; image compression techniques; multiple nonorthogonal bases functions representation; reconstruction quality; split vector quantization technique; still image compression; vector quantization technique; Adaptive algorithm; Bandwidth; Bit rate; Image coding; Image reconstruction; Image representation; Image storage; Speech coding; Transform coding; Vector quantization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signals, Systems and Computers, 2004. Conference Record of the Thirty-Eighth Asilomar Conference on
Print_ISBN :
0-7803-8622-1
Type :
conf
DOI :
10.1109/ACSSC.2004.1399414
Filename :
1399414
Link To Document :
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