Color image enhancement based on rough set and adaptive genetic algorithm

Zhuang Wu
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引用次数: 2

Abstract

The paper combines rough set theory and adaptive genetic algorithm to enhance color image. First, regard the image as a knowledge system, and adopt classification method of rough set theory to combine image color attribute and noise attribute to classify the image, and then come into image boundary region and apply different enhancement algorithms to enhance the image. During rough set classification, use adaptive genetic algorithm to optimize threshold to obtain a best classification result. As image enhancement can be effectively carried out through practical application and verification, therefore, such algorithm has some certain application value.
基于粗糙集和自适应遗传算法的彩色图像增强
本文结合粗糙集理论和自适应遗传算法对彩色图像进行增强。首先将图像视为一个知识系统,采用粗糙集理论的分类方法结合图像颜色属性和噪声属性对图像进行分类,然后进入图像边界区域,应用不同的增强算法对图像进行增强。在粗糙集分类时,采用自适应遗传算法对阈值进行优化,以获得最佳分类结果。由于通过实际应用和验证可以有效地进行图像增强,因此该算法具有一定的应用价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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