双线性快速模糊增强图像边界检测最新算法  

The Newest Double Linear Fast Algorithm of Image Fuzzy Enhancement Edge Detection

作　　者：韩培友[1] 王鸿 郝重阳[1] 

机构地区：[1]西北工业大学电子与信息工程研究所,西安710072 [2]河南省开封市广播电视大学,开封475000

出　　处：《计算机科学》2004年第6期199-200,F004,共3页Computer Science

基　　金：国家重点验室基金资助(51473080101)

摘　　要：本文利用广义模糊集(GFS)理论,给出了全新的用于模糊增强图像区域对比度的线性广义模糊算子(LGFO),从而给出了双线性快速模糊增强图像边界检测最新算法。首先利用线性右半梯形隶属变换将灰度图像的普通空间变换为广义模糊空间,再利用LGFO对广义模糊空间进行区域对比度增强,然后把增强后的广义模糊空间变换为普通空间,最后对处理后的普通空间进行边界提取。通过大量实例验证,使用本文算法提取图像边界速度快、效果好,而且多项指标均超过了文[1～4]。This paper gives the linear general fuzzy operator (LGFO)of fuzzy enhancement of contrast among successive region,then puts forward the newest double linear fast algorithm of image enhancement edge detection use theory of GFS. First the normal space of grey image is translated to correspondent generalized fuzzy space by using right semi-trapezoid membership transform, second proceeds fuzzy enhancement of contrast among successive region to GFS, and then translates GFS to normal space, at last the edge is extracted for normal space. Through a great deal of instance checked, by using this algorithm to extract the edge is fast for velocity and good for effect, all exceeded literature [1～4] on multi-index.

关 键 词：边界检测 模糊增强 广义模糊集 线性广义模糊算子 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]