图像对比度增强的自适应模糊方法

Vikas Singh, A. Pati, V. C. Pal
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引用次数: 0

摘要

图像的对比度对于区分物体与其他物体和背景,特别是对关键信息的分析和诊断起着至关重要的作用。对比度增强提高了任何主观评价的图像质量。本文提出了一种新的基于模糊的对比度增强技术。该方法利用绝对亮度差(ALD)来确定对比度增强的阈值。我们使用高斯模糊隶属函数来找到相应像素的合适权值。高斯隶属函数的均值是用k-middle的均值来确定的,窗口中MF的方差是通过取均值的平均偏差来评估的。该方法在标准数据集上进行了验证,并与各种最新方法进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Adaptive Fuzzy Approach for Image Contrast Enhancement
The contrast of an image plays a crucial role in distinguishing the object from the other objects and the background, especially for analyzing and diagnosing essential information. Contrast enhancement improves the quality of the image for any subjective evaluation. This paper presents novel fuzzy- based techniques for contrast enhancement. In the developed method, absolute luminance difference (ALD) have utilized to decide the threshold for contrast enhancement. We have used Gaussian fuzzy membership function to find the appropriate weight corresponding to the pixels. The mean of the Gaussian membership function is determined using the means of k-middle, and the variance of the MF in a window is evaluated by taking the average deviation from the mean. The proposed approach is validated on the standard datasets and compared with various state-of-the-art methods.
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