Contrast enhancement using brightness preserving bi-histogram equalization
Contrast enhancement using brightness preserving bi-histogram equalization
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DOI：
10.1109/30.580378
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发表时间：
1997-02-01
影响因子：
4.3
通讯作者：
Kim, YT
中科院分区：
文献类型：
--
作者：
Kim, YT
直方图均衡化由于其简单的功能和有效性，在各种应用中被广泛用于对比度增强。例如医学图像处理和雷达信号处理。直方图均衡化的一个缺点是图像的亮度在直方图均衡化后可以改变，这主要是由于直方图均衡化的平坦性。因此，它很少用于消费电子产品中，例如电视，在这些产品中，为了不引入不必要的视觉恶化，可能需要保持原始输入亮度。为了克服直方图均衡化的缺点，提出了一种新的直方图均衡化方法。该算法的基本思想是在两个子图像上分别使用独立的直方图均衡化，该直方图均衡化是根据输入图像的均值对输入图像进行分解得到的，但所得到的均衡化后的子图像在输入均值附近彼此有界。将从数学上证明，与典型的直方图均衡化相比，所提出的算法在增强对比度的同时显著地很好地保持了给定图像的平均亮度，从而提供了许多可用于消费电子产品的自然增强。
Histogram equalization is widely used for contrast enhancement in a variety of applications due to its simple function and effectiveness. Examples include medical image processing and radar signal processing. One drawback of the histogram equalization can be found on the fact that the brightness of an image can be changed after the histogram equalization, which is mainly due to the flattening property of the histogram equalization. Thus, it is rarely utilized in consumer electronic products such as TV where preserving original input brightness may necessary in order not to introduce unnecessary visual deterioration. This paper proposes a novel extension of histogram equalization to overcome such drawback of the histogram equalization. The essence of the proposed algorithm is to utilize independent histogram equalizations separately over two subimages obtained by decomposing the input image based on its mean with a constraint that the resulting equalized subimages are bounded by each other around the input mean. It will be shown mathematically that the proposed algorithm preserves the mean brightness of a given image significantly well compared to typical histogram equalization while enhancing the contrast and, thus, provides much natural enhancement that can be utilized in consumer electronic products.