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Hybrid Classified Vector Quantisation and Its Application to Image Compression

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4 Author(s)
Al-Fayadh, A. ; Liverpool John Moores Univ., Liverpool ; Hussain, A.J. ; Lisboa, P. ; Al-Jumeily, D.

A novel image compression technique using classified vector quantiser and singular value decomposition is presented for the efficient representation of still images. The proposed method is called hybrid classified vector quantisation. A simple but efficient classifier based gradient method which employs only one threshold to determine the class of the input image block that results in a good image quality was utilised. Singular value decomposition method was used for efficient generation of the classified codebooks. The proposed technique was benchmarked with a standard vector quantiser generated using the k-means algorithm, and JPEG-2000. Simulation results indicated 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.

Published in:

EUROCON, 2007. The International Conference on "Computer as a Tool"

Date of Conference:

9-12 Sept. 2007