Self organizing map and wavelet based image compression

被引：12

作者：

Kathirvalavakumar, T. ^{[1
]}

Ponmalar, E. ^{[2
]}

机构：

[1] VHNSN Coll, Dept Comp Sci, Virudunagar 626001, India

[2] SFR Coll women, Dept Comp Sci, Sivakasi 626123, India

来源：

INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS | 2013年 / 4卷 / 04期

关键词：

Neural network; SOM; Wavelet transform; Approximation coefficients; Decompression; VECTOR QUANTIZER; PERFORMANCE; NETWORK;

D O I：

10.1007/s13042-012-0099-3

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The proposed work is hybridizing self organizing map (SOM) and wavelet transform for performing image compression. The novelty in this work is applying discrete wavelet transform (DWT) on the code vector obtained from SOM after vector quantization and storing only the approximation coefficients along with the index values of the SOM. The experimental results of the proposed method show better compression and better peak signal to noise ratio (PSNR) value of the decompressed image.

引用

页码：319 / 326

页数：8

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