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Ri是去模糊之后的特征图, 那么如果用laplacian算子得到pRi特征图范数应该是更大的,因为边缘化更突出.不知道为什么这里写的是将pRi作为目标函数最小化去优化.
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你好,我们通常认为在频域上去模糊会(因除0)导致出现额外的artifacts或者噪声。因此最小化Ri的梯度作为目标函数可以使输出的图像相对噪声和artifacts较小。且约束条件保证了Ri是我们需要的干净图像。
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理解了,谢谢大佬
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Ri是去模糊之后的特征图, 那么如果用laplacian算子得到pRi特征图范数应该是更大的,因为边缘化更突出.不知道为什么这里写的是将pRi作为目标函数最小化去优化.
The text was updated successfully, but these errors were encountered: