CLASSIFIED FREQUENCY SENSITIVE SELF-ORGANIZING MAPS ALGORITHM BASED ON VARIANCE THRESHOLD

被引：0

作者：

Chen, Dongmei ^{[1
]}

Li, Hongsong ^{[1
]}

机构：

[1] Guilin Univ Elect Technol, Coll Informat & Commun, Guilin, Guangxi, Peoples R China

来源：

3RD INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND COMPUTER SCIENCE (ITCS 2011), PROCEEDINGS | 2011年

关键词：

artificial neural network; self-organization mapping; image coding;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper presents a new CFSOM (classified frequency sensitive self-organization mapping) algorithm based on self-organization mapping (SUM) and its improved algorithm that is frequency sensitive self-organization mapping (FSOM) algorithm. The CFSOM algorithm can consider the edge feature and high-frequency detail of the tested image. Experiment results shows that the peak signal-to-noise ratio (PSNR) of the reconstructed image using CFSOM algorithm is higher than that using SUM and FSOM algorithm, that is the reconstructed image quality with CFSOM algorithm has better than that with SUM and FSOM algorithm.

引用

页码：516 / 518

页数：3