Vector quantization fast search algorithm using hyperplane based k-dimensional multi-node search tree

A vector quantization fast search algorithm using hyperplane based k-dimensional multi-node search tree is presented. Misclassification problem associated with hyperplane decision is eliminated by a multi-level back-tracing algorithm. The vector quantization complexity is further lowered by a novel...

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Main Authors: Alton, Kam-Fai Chan, Kam-Tim Woo, Chi-Wah Kok
Format: Conference Proceeding
Language:English
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Acoustics
Airplanes
Barium
Boats
PSNR
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Kam-Tim Woo
Chi-Wah Kok
description A vector quantization fast search algorithm using hyperplane based k-dimensional multi-node search tree is presented. Misclassification problem associated with hyperplane decision is eliminated by a multi-level back-tracing algorithm. The vector quantization complexity is further lowered by a novel relative distance quantization rule. Triangular inequality is applied to lower bound the search distance, thus eliminated all the sub-tree in the k-dimensional search tree during back-tracing. Vector quantization image coding results are presented which showed the proposed algorithm outperform other algorithms in literature both in PSNR and computation time.
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subjects Abstracts
Acoustics
Airplanes
Barium
Boats
PSNR
title Vector quantization fast search algorithm using hyperplane based k-dimensional multi-node search tree
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