Pytorch implementation of MS-SSIM L1 Loss function for image restoration. How to use import this .py file into your project. from MS_SSIM_L1_loss import MS_SSIM_L1_LOSS criterion = MS_SSIM_L1_LOSS() # your pytorch tensor x, y with [B, C, H, W] dimension on cuda device 0 loss ...
实际上,SAD算法与MAD算法思想几乎是 阅读论文《Loss Functions for Image Restoration With Neural Networks》 ,L1损失函数获得的图像质量会更好。这里论文调研了L1损失,SSIM和MS-SSIM,并将L1损失函数和MS-SSIM结合起来构建新的损失函数。但是目前为止,基于SSIM的指标还没有应用到损失函数中...;xy+C2σx2+σy2+C...
It is inspired by human perception and according to a couple of papers, it is a much better loss-function compared to l1/l2. For example, see Loss Functions for Neural Networks for Image Processing. Up to now, I could not find an implementation in TensorFlow. And after trying to do it...