Fractal Image Compression Using Self-Organizing Mapping
Fractal Image Compression Using Self-Organizing Mapping作者机构：Department of Mathematics and Computer Science Faculty of Science Ibb University Ibb Yemen Department of Mathematics Faculty of Sciences and Arts Nauran University KSA Department of Mathematics Faculty of Ibn Alhaitham for Education Baghdad University Baghdad Iraq
出 版 物：《Applied Mathematics》 (应用数学（英文）)
年 卷 期：2014年第5卷第12期
页 面：1810-1819页
学科分类：081203[工学-计算机应用技术] 08[工学] 0835[工学-软件工程] 0812[工学-计算机科学与技术（可授工学、理学学位）]
主 题：Fractal Image Compression Organizing Mapping
摘 要：One of the main disadvantages of fractal image data compression is a loss time in the process of image compression (encoding) and conversion into a system of iterated functions (IFS). In this paper, the idea of the inverse problem of fixed point is introduced. This inverse problem is based on collage theorem which is the cornerstone of the mathematical idea of fractal image compression. Then this idea is applied by iterated function system, iterative system functions and grayscale iterated function system down to general transformation. Mathematical formulation form is also provided on the digital image space, which deals with the computer. Next, this process has been revised to reduce the time required for image compression by excluding some parts of the image that have a specific milestone. The neural network algorithms have been applied on the process of compression (encryption). The experimental results are presented and the performance of the proposed algorithm is discussed. Finally, the comparison between filtered ranges method and self-organizing method is introduced.
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