Transform-Based Vector Quantization Using Bitmap Search Algorithms

Jar-Ferr YANG  Yu-Hwe LEE  Jen-Fa HUANG  Zhong-Geng LEE  

IEICE TRANSACTIONS on Information and Systems   Vol.E83-D   No.12   pp.2113-2121
Publication Date: 2000/12/25
Online ISSN: 
Print ISSN: 0916-8532
Type of Manuscript: PAPER
Category: Image Processing, Image Pattern Recognition
vector quantization,  bitmap search,  binary adder,  singular value decomposition,  

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In this paper, we propose fast bitmap search algorithms to reduce the computational complexity of transform-based vector quantization (VQ) techniques, which achieve better quality in reconstructed images than the ordinary VQ. By removing the unlikely codewords in each step, the bitmap search method, which starts from the most significant bitmap then the successive significant ones, can save more than 90% computation of the ordinary transformed VQ. By applying to the singular value decomposition (SVD) VQ as an example, theoretical analyses and simulation results show that the proposed bitmap search methods dramatically reduce the computation and achieve invisible distortion in the reconstructed images.