一种新的模糊对比度增强算法

Novel fuzzy contrast enhancement algorithm

提出了一种新的基于模糊集合理论的图像模糊对比度增强算法 .首先将图像从灰度域变换到模糊域 ;在预先设定图像空间像素模糊隶属度基础上引入了模糊对比度概念 ,而后在模糊域对模糊对比度进行非线性变换 ,得到增强后的模糊隶属度 ,最后将图像从模糊域变换到灰度域 .由算法分析可知 ,利用模糊隶属度可以对图像的细节进行增强 ,图像的层次更加分明 .通过对几例图像增强对比实验结果的分析 ,表明该算法是有效的 .

An image fuzzy contrast enhancement algorithm based on fuzzy theory is presented. The image gray-level plane is transformed into fuzzy plane and the concept of fuzzy contrast is introduced based on the fact that the fuzzy membership value of each pixel regarding to a predefined image property is preset. The value of fuzzy contrast is modified through nonlinear transformation and the new membership values are generated. The new membership values are re-transformed in the gray-level plane to generate modified gray-levels. The analysis of the algorithm shows that local regions of the image are enhanced by using the concept of the fuzzy contrast to make image clearer. Experiments were conducted on real pictures, and the results show that the approach presented herein performs well.