A New Multistage Lattice Vector Quantization with Adaptive Subband Thresholding for Image Compression. (23rd April 2007)

• Record Type: Journal Article
• Authors: Salleh Salleh, M. F. M. M. F. M.; Soraghan Soraghan, J. J.
• Other Names: Chen Chen Liang-Gee Liang-Gee Academic Editor.
• Is Part Of: EURASIP journal on advances in signal processing. Volume 2007(2007)
• Publication Date: 2007-04-23
• Subjects: Signal processing -- Periodicals; Traitement du signal; Signal processing; Periodicals; 621.3822
• DOI: 10.1155/2007/92928
• Languages: English
• ISSNs: 1687-6172

Abstract

Abstract : Lattice vector quantization (LVQ) reduces coding complexity and computation due to its regular structure. A new multistage LVQ (MLVQ) using an adaptive subband thresholding technique is presented and applied to image compression. The technique concentrates on reducing the quantization error of the quantized vectors by "blowing out" the residual quantization errors with an LVQ scale factor. The significant coefficients of each subband are identified using an optimum adaptive thresholding scheme for each subband. A variable length coding procedure using Golomb codes is used to compress the codebook index which produces a very efficient and fast technique for entropy coding. Experimental results using the MLVQ are shown to be significantly better than JPEG 2000 and the recent VQ techniques for various test images.