COMBINED TECHNIQUES OF SINGULAR-VALUE DECOMPOSITION AND VECTOR QUANTIZATION FOR IMAGE-CODING

被引：69

作者：

YANG, JF ^{[1
]}

LU, CL ^{[1
]}

机构：

[1] IND TECHNOL RES INST,COMP & COMMUN RES LAB,HSINCHU,TAIWAN

来源：

IEEE TRANSACTIONS ON IMAGE PROCESSING | 1995年 / 4卷 / 08期

关键词：

D O I：

10.1109/83.403419

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The combination of singular value decomposition (SVD) and vector quantization (VQ) is proposed as a compression technique to achieve low bit rate and high quality image coding, Given a codebook consisting of singular vectors, two algorithms, which find the best-fit candidates without involving the complicated SVD computation, are described, Simulation results show that tbe proposed methods are better than the discrete cosine transform (DCT) in terms of energy compaction, data rate, image quality, and decoding complexity.

引用

页码：1141 / 1146

页数：6

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