0b8aff0438617c055eb55f0ba5d226fa-Supplemental.pdf

Inthis supplemental material, wefirst present thedetailed networkarchitecture andparameters of the proposed approach in Sec. A. We further provide more analysis of the proposed method and ablation studies in Sec. B. Section C shows some qualitative results for potential applications of the proposed approach on medical imaging and imaging in astronomy. Figure 6: Illustration of learned deep features.(a) The blurry input and ground truth are shown in Figure 1(a)-(b). However, on may actually wonder whether the feature extraction network acts as a denoiser, leading to the observed robustness of the proposed method to various noise levels.