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Paper data
Vector Quantization Fast Search Algorithm using Hyperplane Based k-dimensional Multi-node Search Tree

Chan Kam-Fai, HKUST
Woo Kam-Tim, HKUST
Kok Chi-Wah, HKUST

Page numbers in the proceedings:
Volume I pp 265-268

Source Coding

Paper abstract
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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