DocumentCode :
3109212
Title :
Contrast Sensitive Epsilon-SVR and its application in image compression
Author :
Tolambiya, Arvind ; Kalra, Prem K.
Author_Institution :
Dept. of Electr. Eng., Indian Inst. of Technol. Kanpur, Kanpur
fYear :
2008
fDate :
12-15 Oct. 2008
Firstpage :
359
Lastpage :
364
Abstract :
This paper presents a practical and effective image compression system based on wavelet decomposition and contrast sensitive-SVR (support vector regression) for compressing still images. The kernel function in an SVR plays the central role of implicitly mapping the input vector (through an inner product) into a high-dimensional feature space. We study the different wavelet kernel for image compression application. Image quality is measured objectively, using peak signal-to-noise ratio, and subjectively, using perceived image quality. The effects of different wavelet kernels, image contents and compression ratios are assessed. A comparison with JPEG, SPIHT compression system is given. Our results provide a good reference to choose a suitable kernel for image compression application.
Keywords :
image coding; regression analysis; support vector machines; wavelet transforms; contrast sensitive epsilon-SVR; image compression; image quality; kernel function; peak signal-to-noise ratio; support vector regression; wavelet decomposition; Compression algorithms; Discrete cosine transforms; Discrete wavelet transforms; Image coding; Image quality; Image reconstruction; Image storage; Kernel; Support vector machines; Transform coding; Image compression; Support vector regression (SVR); kernel machines; wavelet kernels;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man and Cybernetics, 2008. SMC 2008. IEEE International Conference on
Conference_Location :
Singapore
ISSN :
1062-922X
Print_ISBN :
978-1-4244-2383-5
Electronic_ISBN :
1062-922X
Type :
conf
DOI :
10.1109/ICSMC.2008.4811302
Filename :
4811302
Link To Document :
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