Kumaraswamy Distribution Based Bi-histogram Equalization for Enhancement of Microscopic Images

M. Suresha, D. Raghukumar, Subramanya Kuppa
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引用次数: 1

Abstract

Among all image enhancement techniques, histogram equalization is the most used technique. However, preserving brightness is the main issue, and it creates a weird look by destroying its originality. This paper proposes a new method that has command on the brightness issue of histogram equalization to enhance the quality of microscopic images. The method splits the histogram of each color channel into two sub-histograms based on their mean as the threshold and supplanting their cumulative distribution with Kumaraswamy distribution. The proposed method is tested with color microscopic images of cancer-affected lymph nodes gathered from Biological Image Repository IICBU, and objective and subjective assessments confirm that the proposed approach performs more efficiently compared to other state-of-the-art methods.
基于Kumaraswamy分布的双直方图均衡化显微图像增强
在所有的图像增强技术中,直方图均衡化是最常用的技术。然而,保持亮度是主要问题,它破坏了它的原创性,造成了奇怪的外观。本文提出了一种新的方法来解决直方图均衡化的亮度问题,以提高显微图像的质量。该方法将每个颜色通道的直方图以其均值为阈值分割成两个子直方图,并用Kumaraswamy分布代替它们的累积分布。采用生物图像库IICBU收集的癌症影响淋巴结的彩色显微图像对所提出的方法进行了测试,客观和主观评估证实,与其他最先进的方法相比,所提出的方法更有效。
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