双线性广义模糊增强边界图像检测算法

A Bilinear Generalized Fuzzy Enhancement Algorithm to Image Edge Detection

在模糊集和广义模糊集理论的基础上 ,给出了用于模糊增强图像区域对比度的线性广义模糊算子 ,实现了图像的双线性快速无损边界检测算法 该算法利用线性左半梯形模糊分布函数和线性广义模糊算子实现灰度图像空间、普通模糊空间和广义模糊空间之间的转换 ,同时对广义模糊空间进行区域对比度增强 ,最后在灰度图像空间中提取边界 大量实例表明 :利用文中算法提取图像边界速度快、效果好 ,并且在多项指标上均超过了Pal算法。

This article presents a linear generalized fuzzy operator (LGFO)for fuzzy enhancement of contrast among successive region,and then puts forward a novel bilinear nondestructive algorithm for image edge detection based on the theory of normal fuzzy sets(NFS)and generalized fuzzy sets(GFS). The principle of this algorithm is to achieve space transform among grey image space, normal fuzzy space, and generalized fuzzy space by using left semi-trapezoid fuzzy distribution function and LGFO. By the algorithm, the contrast among successive region for generalized fuzzy space is enhanced fuzzily in the process of space transform. Then the edge is extracted in grey image space. Experiments indicate that by using the algorithm proposed in the paper, extraction of edge is efficient and good in effect, superior to the algorithm of Pal, Chen Wufan and Wang Hui in multi-index.