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A fuzzy histogram weighting method for efficient image contrast enhancement

机译:一种用于高效图像对比度增强的模糊直方图加权方法

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摘要

Image contrast enhancement is an important step in digital image processing applications. In this paper, we present an efficient contrast enhancement approach, which employs a histogram weighting method based on fuzzy system. It is able to enhance the contrast of input images while preserving their details. The proposed method divides the histogram of the original image into three sub-histograms using Fuzzy clustering. The obtained sub-histograms are weighted based on the Mamdani Fuzzy inference system, and then they are summed to generate a new histogram. The produced histogram is modified to reduce undesirable effects of its spikes and pits. Finally, the enhanced image is obtained by equalization of the modified histogram. The Mamdani fuzzy inference system assigns an appropriate dynamic range to each input interval of gray levels (sub-histogram), hence enhancing the image details. Experimental results for different types of images verified the merit of the proposed method in terms of preservation the input image details and improving its contrast.
机译:图像对比度增强是数字图像处理应用的重要步骤。在本文中,我们提出了一种有效的对比度增强方法,其采用基于模糊系统的直方图加权方法。它能够在保留其细节时增强输入图像的对比度。该方法使用模糊聚类将原始图像的直方图划分为三个子直方图。基于Mamdani模糊推理系统加权所获得的子直方图,然后总结它们以生成新的直方图。产生的直方图被修改为减少其尖峰和凹坑的不期望的影响。最后,通过修改直方图的均衡获得增强的图像。 Mamdani模糊推理系统将适当的动态范围分配给灰度级的每个输入间隔(子直方图),因此增强图像细节。在保护输入图像细节和改善其对比度方面,不同类型图像的实验结果验证了所提出的方法的优点并提高其对比度。

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