Fractal Image Compression With Adaptive Quardtree Partitioning And Archetype Classification

被引：0

作者：

Nandi, Utpal ^{[1
]}

Mandal, Jyotsna Kumar ^{[2
]}

机构：

[1] Vidyasagar Univ, Dept Comp Sci, Medinipur, W Bengal, India

[2] Univ Kalyani, Dept Comp Sci & Engn, Kalyani, W Bengal, India

来源：

2015 IEEE INTERNATIONAL CONFERENCE ON RESEARCH IN COMPUTATIONAL INTELLIGENCE AND COMMUNICATION NETWORKS (ICRCICN) | 2015年

关键词：

archetype; quardtree partitioning; adaptive quardtree partitioning; Fractal compression; Compression ratio;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, a novel fractal image compression with adaptive quardtree partitioning scheme is proposed. The technique classifies ranges and domains using a different classification method known as archetype classification that significantly reduces the mean square error (MSE) computations during encoding. Performance of the proposed technique in terms of compression ratios and fidelity versus encoding time data are compared with fractal image compression with quardtree partitioning scheme and fractal image compression with adaptive quardtree partitioning scheme.

引用

页码：56 / 60

页数：5

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