一种基于粗糙集分类的图像增强方法  

Image Enhancement Method Based on Rough Sets Classification

作　　者：蒋加伏[1] 刁洪祥[1] 唐贤瑛[1] 

机构地区：[1]长沙交通学院计算机工程系,长沙410076

出　　处：《计算机工程与应用》2003年第19期109-110,共2页Computer Engineering and Applications

基　　金：湖南省自然科学基金资助(编号:00JJY2059)

摘　　要：该文利用两个特征值属性,图像块的低高频能量和图像块的频域熵对图像进行粗糙集分类,得到边缘区域集合和平滑区域集合。然后分别对边缘区域和平滑区域做模糊增强和邻域平均法平滑,最后将图像重构得到边缘增强的图像,从而使图像的边缘变得更加清晰。In this paper,two feature attributes that are low and high frequency energy and frequency domain entropy are applied to classify the image based on rough sets,and the edge block and plain block are obtained.Then the paper carries on fuzzy enhancement and smooth handle of neighborhood respectively.At last,the paper obtains the image of edge enhancement ,and makes the edge of image more distinct.

关 键 词：粗糙集 图像增强 模糊增强 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]