Histogram partition based gamma correction for image contrast enhancement

Dongni Zhang, W. Park, Seung-Jun Lee, Kang-A. Choi, S. Ko
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引用次数: 26

Abstract

This paper presents an adaptive image contrast enhancement method. The proposed method is based on a local gamma correction piloted by histogram analysis. First, the image histogram is partitioned based on the local minima and the mean gray-level of each partition is calculated. Then, gamma correction is performed using the resulted mean gray-levels. By analyzing the partitioned histograms, the parameters are automatically adjusted. Experimental results show that both good contrast enhancement performance and image brightness preservation can be achieved by the proposed method.
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基于直方图分割的图像对比度增强伽马校正
提出了一种自适应图像对比度增强方法。该方法基于直方图分析的局部伽玛校正。首先,基于局部极小值对图像直方图进行分割,并计算各分割的平均灰度值;然后,伽玛校正使用结果的平均灰度级执行。通过分析分割后的直方图,自动调整参数。实验结果表明,该方法既能获得较好的对比度增强效果,又能保持图像的亮度。
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