基于动态聚类的直方图均衡化图像增强
Image Enhancement via Dynamic Clustering based Histogram Equalization
直方图均衡化能够均衡图像的灰度级范围，是一种经典有效的方法，但对于CT类的低灰度区域有较多信息的图像，直方图均衡化可能会使图像出现过分曝光而丢失细节，从而本文提出了通过动态聚类方法对图像直方图进行处理，然后分别对处理后的若干个灰度区域进行直方图均衡化的方法，对CT类图像有较好的增强效果。
Histogram equalization (HE), a classic and efficient method, can extend the grey scale of images. But for low gray level distributed images such as CT images, histogram equalization may make the image over-exposure and lost details of information. This paper presents a method, which separates the histogram of image pixels into several regions by dynamic clustering methods and equalizes each region respectively. This method is more effective for the image such as CT images.
朱姣、张艳艳、曹燕华
电子技术应用
动态聚类直方图均衡化图像增强图像
dynamic clusteringhistogram equalizationimage enhancementimages
朱姣,张艳艳,曹燕华.基于动态聚类的直方图均衡化图像增强[EB/OL].(2010-04-13)[2025-08-03].http://www.paper.edu.cn/releasepaper/content/201004-420.点此复制
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