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A new adaptive contrast enhancement algorithm for infrared images based on double plateaus histogram equalization

机译:基于双高原直方图均衡化的红外图像自适应对比度增强新算法

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摘要

In infrared images, detail pixels are easily immerged in large quantity of low-contrast background pixels. According to these characteristics, an adaptive contrast enhancement algorithm based on double plateaus histogram equalization for infrared images was presented in this paper. Traditional double plateaus histogram equalization algorithm used constant threshold and could not change the threshold value in various scenes, so that its practical usage is limited. In the proposed algorithm, the upper and lower threshold value could be calculated by searching local maximum and predicting minimum gray interval and be updated in real time. With the proposed algorithm, the background of infrared image was constrained while the details could also be enhanced. Experimental results proved that the proposed algorithm can effectively enhance the contrast of infrared images, especially the details of infrared images.
机译:在红外图像中,细节像素很容易浸入大量低对比度的背景像素中。根据这些特点,提出了一种基于双高原直方图均衡化的红外图像自适应对比度增强算法。传统的双高原直方图均衡算法使用恒定的阈值,无法在各种场景下改变阈值,因此其实际应用受到限制。在所提出的算法中,可以通过搜索局部最大值和预测最小灰度间隔来计算上下阈值,并实时更新。提出的算法在约束红外图像背景的同时,还可以增强细节。实验结果表明,该算法可以有效提高红外图像的对比度,尤其是红外图像的细节。

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