一种改进的保亮度动态直方图均衡化方法

Fan Yang, Renjie Li
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引用次数: 0

摘要

直方图均衡化是提高图像对比度的一种有效的图像增强方法,目前已经发展了几种均衡化方法。保持亮度动态直方图均衡化(BPDHE)是一种基于子直方图的均衡化方法,在某些图像直方图的分割过程中,以及在保持图像结构和信息熵方面,BPDHE都有优化性能的余地。为此,本文提出了一种改进BPDHE的方法。首先,对图像进行双线性插值。然后,将图像灰度的概率密度函数根据其均值分为两部分。最后,用不同的方法求出这两部分的局部最大值。本文采用绝对平均亮度误差(AMBE)、结构相似指数度量(SSIM)、信息熵(Entropy)和峰值信噪比(PSNR)对不同方法进行了比较。结果表明,本文提出的方法在保持图像亮度的同时,有效地增强了图像的对比度。在样本图像评价指标的平均值中,SSIM、Entropy和PSNR分别比BPDHE高0.219、2.0811和6.6201。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Improved Method for Brightness Preserving Dynamic Histogram Equalization
Histogram equalization is an effective image enhancement method for improving image contrast, and several equalization methods have been developed. Brightness-preserving dynamic histogram equalization (BPDHE) is a sub-histogram-based equalization method, and there is scope for optimising the performance of BPDHE in the segmentation process of some image histograms and in maintaining image structure and information entropy. Therefore, this paper presents a method to improve BPDHE. First, the image is subjected to bilinear interpolation. Then, the probability density function of the grey level of the image is divided into two parts according to its mean value. Finally, different methods are used to find local maximums for each of these two parts. In this paper, Absolute Mean Brightness Error (AMBE), Structure Similarity Index Measure (SSIM), Information Entropy (Entropy) and Peak Signal to Noise Ratio (PSNR) are used to compare with the different methods. The results show that the method proposed in this paper effectively enhances the contrast of the image while preserving the image brightness. In the average of evaluation metrics of the sample images, SSIM, Entropy and PSNR were 0.219, 2.0811 and 6.6201 higher than those of BPDHE, respectively.
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