Generalized Differential Gray-level Histogram Equalization

2019 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS) Pub Date : 2019-12-01 DOI:10.1109/ISPACS48206.2019.8986331

Hideaki Tanaka, A. Taguchi

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Abstract

Histogram equalization (HE) is a simple and effective method for contrast enhancement as it can automatically define the gray-level transformation function based on the distribution of gray-level included in the image. HE fails to produce satisfactory results for broad range of low-contrast images because the HE does not use a spatial feature included in the input image. The differential gray-level histogram which is contained edge information of the input image, were defined. Furthermore, the differential gray-level histogram equalization (DHE) has been proposed. The DHE shows better enhancement results compared to the HE results for many kinds of images. In this paper, we propose a generalized DHE (GDHE) method. In GDHE, histograms are created using powers of gradients. If the power is set as 0, GHE is equivalent to HE, and if the power is set as 1, GHE is equivalent to DHE. That is, GDHE includes HE and DHE. GHE can preserve the mean brightness of the input image perfectly by setting the power appropriately and shows good contrast enhancement results at the same time.

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广义差分灰度直方图均衡化

直方图均衡化(Histogram equalization, HE)是一种简单有效的对比度增强方法，它可以根据图像中包含的灰度分布自动定义灰度变换函数。对于大范围的低对比度图像，HE不能产生令人满意的结果，因为HE没有使用输入图像中包含的空间特征。定义了包含输入图像边缘信息的差分灰度直方图。此外，还提出了差分灰度直方图均衡化(DHE)方法。DHE对多种图像的增强效果优于HE。本文提出了一种广义DHE (GDHE)方法。在GDHE中，直方图是使用梯度幂创建的。如果功率设置为0，则GHE相当于HE，如果功率设置为1，则GHE相当于DHE。也就是说，GDHE包括HE和DHE。通过适当设置功率，GHE可以很好地保持输入图像的平均亮度，同时显示出良好的对比度增强效果。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2019 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)

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