Supplementary Material of " Res Shift: Efficient Diffusion Model for Image Super-resolution by Residual Shifting "

Derivation of Eq. (6): According to Bayes's theorem, we have q ( x Please zoom in for a better view. The blurring kernel is randomly sampled from the isotropic Gaussian and anisotropic Gaussian kernels with a probability of [0.6, 0.4]. For isotropic Gaussian kernel, the kernel width is uniformly sampled from [0.2, 0.8]. We first added Gaussian and Poisson noise with a probability of [0.5, 0.5]. For Gaussian noise, the noise level is randomly chosen from [1,15].