Title :
WSVM with Morlet Wavelet Kernel for Image Compression
Author :
Tolambiya, Arvind ; Kalra, Prem K.
Author_Institution :
Indian Inst. of Technol., Kanpur
Abstract :
In this paper, we presented a practical and effective image compression system based on Wavelet Support Vector Machine (WSVM) with Morlet wavelet kernel for compressing still images. The algorithm combines WSVM learning with discrete wavelet decomposition technique. Compression is achieved by approximating wavelet coefficients at each subband separately using WSVM regression. Results demonstrate in comparison with JPEG, SPIHT and SVM with Gaussian kernel algorithm, the proposed algorithm increases compression ratio for a given image quality; conversely it gives better image quality for a given compression ratio.
Keywords :
data compression; discrete wavelet transforms; image coding; learning (artificial intelligence); support vector machines; Morlet wavelet kernel; WSVM learning; discrete wavelet decomposition technique; image compression; wavelet support vector machine; Discrete cosine transforms; Discrete wavelet transforms; Image coding; Image quality; Image reconstruction; Image storage; Kernel; Support vector machine classification; Support vector machines; Transform coding; Image compression; Morlet wavelet kernel; Wavelet support vector machine (WSVM); kernel machines;
Conference_Titel :
System of Systems Engineering, 2007. SoSE '07. IEEE International Conference on
Conference_Location :
San Antonio, TX
Print_ISBN :
1-4244-1159-9
Electronic_ISBN :
1-4244-1160-2
DOI :
10.1109/SYSOSE.2007.4304322