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Infrared image detail enhancement based on the gradient field specification

机译:基于梯度场规范的红外图像细节增强

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摘要

Human vision is sensitive to the changes of local image details, which are actually image gradients. To enhance faint infrared image details, this article proposes a gradient field specification algorithm. First we define the image gradient field and gradient histogram. Then, by analyzing the characteristics of the gradient histogram, we construct a Gaussian function to obtain the gradient histogram specification and therefore obtain the transform gradient field. In addition, subhistogram equalization is proposed based on the histogram equalization to improve the contrast of infrared images. The experimental results show that the algorithm can effectively improve image contrast and enhance weak infrared image details and edges. As a result, it can give qualified image information for different applications of an infrared image. In addition, it can also be applied to enhance other types of images such as visible, medical, and lunar surface.
机译:人类的视觉对局部图像细节的变化很敏感,这些变化实际上是图像梯度。为了增强微弱的红外图像细节,本文提出了一种梯度场指定算法。首先,我们定义图像梯度场和梯度直方图。然后,通过分析梯度直方图的特征,我们构造了一个高斯函数以获得梯度直方图规格,从而获得了变换梯度场。另外,基于直方图均衡化提出了亚直方图均衡化,以提高红外图像的对比度。实验结果表明,该算法可以有效提高图像对比度,增强弱红外图像的细节和边缘。结果,它可以为红外图像的不同应用提供合格的图像信息。此外,它还可用于增强其他类型的图像,例如可见,医学和月球表面。

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