基于粗糙集的微小缺陷图像对比度增强算法  

Contrast Enhancement Algorithm for Micro Defect Image Based on Rough Set

作　　者：唐爱平[1] 杨丽 TANG Ai-ping;YANG Li(Creative Department,Changzhou Vocational Institute of Textile and Garment,Changzhou 213164,China;School of Information Engineering,Zhengzhou Vocational University of Information and Technology,Zhengzhou 450008,China)

机构地区：[1]常州纺织服装职业技术学院创意学院,江苏常州213164 [2]郑州信息科技职业学院信息工程学院,河南郑州450008

出　　处：《控制工程》2023年第5期881-885,共5页Control Engineering of China

基　　金：江苏省教育厅2018年高职院校工程技术研究开发中心资助项目(苏教科[2018]10号)。

摘　　要：设计了一种微小缺陷图像对比度增强算法。采用粗糙集理论将图像划分为不同类别,同一类别中像素间为不可分辨关系。并依据图像灰度值和噪声属性进一步将图像划分为子图,在子图中得到图像的明暗区域。对图像不同区域进行直方图均衡变换和直方图指数变换处理,处理后即可增强图像的对比度。仿真实验表明,处理后可突出显示图像中的微小细节,图像不同区域之间的划分效果更加明显,可以有效提升图像的对比度和视觉效果。A contrast enhancement algorithm for images with small defects is designed.The rough set theory is used to divide the image into different categories,and the relationship between pixels in the same category are indistinguishable.The image is further divided into sub-images according to the image gray value and noise attributes,and the light and dark areas of the image are obtained in the sub-images.Perform histogram equalization transformation and histogram exponential transformation processing on different areas of the image,and the contrast of the image can be enhanced after processing.Simulation experiment shows that the tiny details in the image can be highlighted,and the division effect between different regions of the image are more obvious,which can effectively improve the contrast of the image and enhance the visual effect.

关 键 词：粗糙集理论 图像对比度 不可分辨关系 信噪比 最大类间方差法 

分 类 号：TP315.2[自动化与计算机技术—计算机软件与理论]