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Enhancement of infrared image using multi-fractal based on human visual system

机译:基于人类视觉系统的多分形的红外图像增强

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A multifractal theory analysis of infrared image is proposed and the multifractal characteristics of edges in the infrared images are extracted. The singularity characteristics of each pixel in the image and its multifractal spectrum are calculated. Then pixels are classified by HVS(human visual system), which is more sensitive to the edge structure of image. From smoothness area to edge area, the pixels are weighted and enhanced. Infrared images are first analyzed using multifractal theory so that singularity α(x, y) of each pixel can be extracted from an infrared image. Multifractal spectrum f(α) is then estimated, which can reflect overall characteristic of an infrared image, and singularity exponent can reflect local characteristic of image so that edge and texture of an infrared image can be accurately extracted based on singularity of each pixel and multifractal spectrum. And finally the edge pixels are classified and enhanced in accordance with the sensitivity of human visual system to the edge profile of an infrared image. Experiments show that the image enhancement method is more available and highlights the human eyes' sensitive image area. The problem of low visibility and blurry edge is resolved efficiently and the enhancement image is more suitable to human's observing.
机译:提出了红外图像的多重分形分析理论并提取在红外图像边缘的多重分形特性。图像中的每个像素及其形谱的奇异性特性被计算。然后像素由HVS(人类视觉系统),这是图像的边缘结构更敏感分类。从平滑性区域的边缘区域,所述像素加权并增强。红外图像是使用多重理论以使得每个像素的那个奇点α(X,Y)可从红外图像中提取第一分析。然后形谱F(α)进行估计,其可以反映的红外图像的整体特性,和奇异性指数可以反映图像的局部特性,从而红外图像的边缘和纹理,可以准确地提取基于每个像素和多重分形的奇点光谱。最后边缘像素被分类,并且根据人类视觉系统对红外图像的边缘轮廓的灵敏度增强。实验表明,该图像增强方法更可用,并强调了人眼敏感的图像区域。低能见度和模糊边缘的问题是有效的解决,并强调图像更适合人类的观测。

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