Title :
Image compression using improved hybrid classified vector quantisation
Author :
Hussain, A.J. ; Al-Fayadh, A. ; Al-Jumeily, D. ; Lisboa, P. ; Liatsis, P.
Author_Institution :
Dept. of Comput. & Math. Sci., Liverpool John Moores Univ.
Abstract :
A novel image compression technique using classified vector quantiser and singular value decomposition is proposed for the efficient representation of still images. The proposed method is called improved hybrid classified vector quantisation. The proposed technique was benchmarked with the standard vector quantiser generated using the k-means algorithm, and JPEG-2000. Simulation results indicate that the proposed approach alleviates edge degradation and can reconstruct good visual quality images with higher peak signal-to-noise ratio than the benchmarked techniques
Keywords :
image coding; image representation; singular value decomposition; vector quantisation; JPEG-2000; classified vector quantiser; edge degradation; hybrid classified vector quantisation; image compression; image reconstruction; k-means algorithm; singular value decomposition; still image representation;
Journal_Title :
Electronics Letters
DOI :
10.1049/el:20073756
