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双边滤波

于 2022-03-30 发布 文件大小:118.08 kB
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过滤也许是图像处理和计算机视觉的最基本运作。广泛意义上的"过滤"一词已过滤的图像的给定位置处的值是输入图像中的值的函数 小邻域内的相同的位置。例如,高斯低通滤波计算像素加权的平均在附近,权重随邻里中心的距离值。虽然正式可以给出 这个重量的下滑定量解释,直觉是图像通常不同地慢慢地走过空间,因此可能有相似的价值观,相邻像素灰度值, 并因此是适当的它们的平均数。噪音腐败这些邻近像素点的值是相互不相关信号值,所以噪声平均带走虽然保留了信号。 空间的缓慢变化的假设失败在边缘,因此模糊的线性低通滤波。我们怎样才能防止跨的边缘,同时仍然平均在光滑的区域内平均?很多的努力已

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