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摘要: 局部对比度在图像融合领域中扮演着重要角色.图像融合的目的是将原图像中的重要信息保留到融合结果中去.韦伯定律告诉我们不同背景下的同样的灰度变化给人的干支是不同的,所以一个理想的图像处理算法必须考虑视觉原理.本文考虑了人类视觉系统(HVS),将量化的主观对比度从源图像保留到融合结果中.利用临界可分辨率(JND)作为量化度量,多通道图像的感知对比度作为融合的目标.构造了一个泛函极值问题来寻找融合结果,使得融合结果的主观对比度尽可能接近我们的目标.使用变分法可以得到Euler-Lagrange方程,然后利用梯度下降的迭代算法来求解.试验结果表明,本文的方法具有很好的主观感知效果.Abstract: Local contrast, or variation, plays an important role in image fusion which is mainly to preserve the important information from the source images to the fusion result. Weber's law tells us that the same variation under different backgrounds will cause different perceptual feelings, thus an ideal image processor has to take into account the effects of vision psychology and psychophysics. This paper considers the property of human visual system (HVS) and transfers the quantitative perceptual variations from each source image to the result. Using just-noticeable-difference (JND) as measurement, the multiband image's perceptual contrast is obtained as a target. We construct a functional extremum problem to find a single band image, or fusion result, which has the closest perceptual contrast to the target one. Via the variational approach, the Euler-Lagrange equation is derived, and a gradient descent iteration is employed. Experimental results show that this method is perceptually good.
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