基于排序选择机制的遗传算法对分形图像进行压缩

A. N. Kulkarni, S. Gandhe, P. Dhulekar, G. Phade
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引用次数: 5

摘要

多年来,对视频序列和计算机动画中的图像的需求急剧增加。这引起了人们对压缩这一重要问题的关注,从而降低了数据存储和传输的成本。对于静止图像压缩,JPEG是世界范围内使用的。但人们也在探索其他方法;分形图像压缩就是其中之一。它是基于图像本身的自相似特性来寻找最佳匹配。此属性用于生成分形代码。提出了一种基于排序选择机制的遗传算法对分形图像进行压缩的新方法。将该算法应用于分形和非分形图像,实验结果表明,在保持图像质量不变的情况下,两类图像的编码时间都大大减少。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fractal image compression using genetic algorithm with ranking select mechanism
The demand for images in video sequences and computer animation has increased drastically over the years. This gives attention on an important issue of compression, resulting into reduction in cost of data storage and transmission. For still image compression JPEG is used world -wide. But alternative methods are also being explored; Fractal image compression is one of them. It is based on the self-similarity property to find out the best match within the image itself. This property is used to generate a fractal code. In this paper, the new approach for fractal image compression using genetic algorithm with ranking select mechanism is proposed. This proposed algorithm is applied on fractal as well as non-fractal images and the experimental result shows that the encoding time for both types of images is greatly reduced while maintaining their quality intact.
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