tailieunhanh - Báo cáo hóa học: " Research Article A New Multistage Lattice Vector Quantization with Adaptive Subband Thresholding for Image Compression"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article A New Multistage Lattice Vector Quantization with Adaptive Subband Thresholding for Image Compression | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2007 Article ID 92928 11 pages doi 2007 92928 Research Article A New Multistage Lattice Vector Quantization with Adaptive Subband Thresholding for Image Compression M. F. M. Salleh and J. Soraghan Institute for Signal Processing and Communications Department of Electronic and Electrical Engineering University of Strathclyde Royal College Building Glasgow G1 1XW UK Received 22 December 2005 Revised 2 December 2006 Accepted 2 February 2007 Recommended by Liang-Gee Chen 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. Copyright 2007 M. F. M. Salleh and J. Soraghan. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. 1. INTRODUCTION Recently there have been significant efforts in producing efficient image coding algorithms based on the wavelet transform and vector quantization VQ 1-4 . In 4 a review of some of image compression schemes that use vector quantization and wavelet transform is given. In 1 a still image compression scheme introduces an adaptive VQ .