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Image contrast enhancement using optimum sub-histograms modification and preserving brightness levels mean without losing image specification

机译:使用最佳子直方图修改并保持亮度水平的图像对比度增强意味着不会丢失图像规格

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Histogram modification is one of the well- known and most effective techniques in increasing contrast and image quality enhancement. But, in some cases, traditional histogram modification would increase image contrast too much and cause image details to be lost. In this article, a new histogram modification method has been proposed that contains a combination of histogram division part and brightness level transferring part. In histogram division part, image histogram will be divide into smaller optimum subunits according to mean value and standard deviation. This division is controlled automatically by using PSNR criterion. In the second part, with applying local cumulative probability distribution function for each of subunits of histogram, we will reach the enhanced image. Experimental results shows that, this method would not only keep visual details of histogram, but also enhance image contrast.
机译:直方图修改是提高对比度和提高图像质量的众所周知且最有效的技术之一。但是,在某些情况下,传统的直方图修改会过多地增加图像对比度,并导致图像细节丢失。在本文中,提出了一种新的直方图修改方法,该方法包含直方图划分部分和亮度级别传递部分的组合。在直方图划分部分,图像直方图将根据平均值和标准偏差分为较小的最佳子单元。通过使用PSNR准则自动控制此划分。在第二部分中,通过对直方图的每个子单元应用局部累积概率分布函数,我们将获得增强的图像。实验结果表明,该方法不仅可以保留直方图的视觉细节,而且可以增强图像对比度。

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