基于模糊熵边缘信息同质性测度的对比度增强

Contrast Enhancement Using the Homogeneous Measurement of Edge Information Based on Fuzzy Entropy

针对传统图像对比度增强方法存在局部区域过增强或增强不足等诸多问题,提出了一种基于模糊熵边缘点特征向量的同质性对比度增强算法.首先提取边缘特征信息,找到基于模糊熵边缘点特征向量的三个本质特征,然后用此来定义同质性,进而利用同质性增强的方法来进行对比度增强,得到增强图像.仿真结果表明:与其他传统的对比度增强方法相比,新方法图像增强效果明显,平均梯度、边缘强度、信息熵、增强度准则(EME)这4个客观标准均得到改善,很好地加强了细节信息.

Abstract ： In view of the problems of excessive or lack enhancement in traditional image contrast enhancement methods,a new homogeneous contrast enhancement algorithm based on fuzzy entropy edge points eigenvectors was proposed. Firstly, the edge feature information was extracted, that is, the three essential characteristics based on fuzzy entropy edge point eigenvectors were found; secondly, homogeneity was defined with the three characteristics; Finally, the image was enhanced by homogeneous contrast enhancement algorithm. The simu- lation results show that, compared with other traditional contrast enhancement methods, the new method ob- tains more obvious images, the average gradient, edge intensity, information entropy, and EME four objec- tive criteria are improved, and the enhanced image with new algorithm obtains better detail information.