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A New Sharpness Measure Based on Gaussian Lines and Edges

机译:基于高斯线和边的新锐度度量

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We measure the sharpness of natural (complex) images using Gaussian models. We first locate lines and edges in the image. We apply Gaussian derivatives at different scales to the lines and edges. This yields a response function, to which we can fit the response function of model lines and edges. We can thus estimate the width and amplitude of the line or edge. As measure of the sharpness we propose the 5th percentile of the sigmas or the fraction of line/edge pixels with a sigma smaller than 1.
机译:我们使用高斯模型测量自然(复杂)图像的清晰度。我们首先在图像中找到线条和边缘。我们对线和边应用不同比例的高斯导数。这产生了一个响应函数,我们可以拟合模型线和边的响应函数。因此,我们可以估计线条或边缘的宽度和幅度。作为清晰度的度量,我们建议sigma的第5个百分位数或sigma小于1的线/边像素的分数。

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