Use Fractal Brown Random theory to enhance infrared image

Tianhe Yu, Xiaoyang Yu, Yinhang Mao, J. Dai
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引用次数: 2

Abstract

Blurring edge of the infrared image is not conducive to human eye observation. In order to improve the visual effect of infrared image and the visibility of infrared image, the theory of fractal Brown is used to enhance infrared image in this paper. Fractal Brown Random(FBR) with the nature of random field shows that small area of the image meet the self-similarity, but the regularity of the boundary of the area is broken, therefore the occurrence of singular boundary value H, infrared image gray surface roughness is described. First calculating the fractal parameters of the image of each pixel, according to the visual sensitive characteristic of the human eyes to classify pixel of an image, which are classified as smooth points and details, and then the pixel are respective weighted enhance. According to the experiment we know that enhanced image highlighted the contour of an object which can obtain a good visual effect. Because the visual characteristic is fully considered in this method, the problem of poor visibility blurred edges of infrared images can be solved.
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利用分形布朗随机理论增强红外图像
红外图像边缘模糊不利于人眼观察。为了提高红外图像的视觉效果和红外图像的可见性,本文利用分形布朗理论对红外图像进行增强。具有随机场性质的分形布朗随机(FBR)表明图像的小区域满足自相似性,但该区域边界的规律性被打破,因此出现奇异边界值H,描述了红外图像的灰度表面粗糙度。首先计算图像各像素点的分形参数,根据人眼的视觉敏感特性对图像像素点进行分类,分别将其分类为光滑点和细节,然后对像素点分别进行加权增强。通过实验可知,增强后的图像突出了物体的轮廓,可以获得良好的视觉效果。该方法充分考虑了红外图像的视觉特性,解决了红外图像可见性差、边缘模糊的问题。
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