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An improved contrast enhancement algorithm for infrared images based on adaptive double plateaus histogram equalization

机译:基于自适应双压力直方图均衡的红外图像改进的对比度增强算法

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摘要

Infrared thermal images can reflect the thermal-radiation distribution of a particular scene. However, the contrast of the infrared images is usually low. Hence, it is generally necessary to enhance the contrast of infrared images in advance to facilitate subsequent recognition and analysis. Based on the adaptive double plateaus histogram equalization, this paper presents an improved contrast enhancement algorithm for infrared thermal images. In the proposed algorithm, the normalized coefficient of variation of the histogram, which characterizes the level of contrast enhancement, is introduced as feedback information to adjust the upper and lower plateau thresholds. The experiments on actual infrared images show that compared to the three typical contrast-enhancement algorithms, the proposed algorithm has better scene adaptability and yields better contrast-enhancement results for infrared images with more dark areas or a higher dynamic range. Hence, it has high application value in contrast enhancement, dynamic range compression, and digital detail enhancement for infrared thermal images. (C) 2018 Elsevier B.V. All rights reserved.
机译:红外线热图像可以反映特定场景的热辐射分布。然而,红外图像的对比度通常很低。因此,通常需要提高红外图像的对比度,以便于随后的识别和分析。基于自适应双功率直方图均衡,本文提出了一种改进的红外热图像对比度增强算法。在所提出的算法中,引入了表征对比度增强水平的直方图的归一化变化系数,作为反馈信息,以调整上下平台阈值。实际红外图像的实验表明,与三个典型的对比度增强算法相比,所提出的算法具有更好的场景适应性,并且对具有更多暗区域或更高的动态范围的红外图像产生更好的对比度结果。因此,它具有对比度增强,动态范围压缩和红外热图像的数字细节增强的高应用价值。 (c)2018 Elsevier B.v.保留所有权利。

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