Self-Adaptively Learning to Demoiré from Focused and Defocused Image Pairs Supplementary Material Lin Liu

We use three cameras and three screens to capture our dataset; please see Table 1 for the specifications. The following algorithms (Procedure 1 and Procedure 2) show the joint optimization method and the baseline alternating optimization method compared in the ablation study in Section 5.1 of the main paper. Procedure 1 The joint optimization algorithm.Input: Focused image M with moiré patterns and defocused blur image B without moiré patterns; Output: Estimated moiré-free image C; Procedure 2 The alternating optimization algorithm.Input: Focused image M with moiré patterns and defocused blur image B without moiré patterns; Output: Estimated moiré-free image C; We also test our model on a smartphone HUA WEI P30 PRO. To test on the real world examples, we do some preprocessing, e.g., alignment. Figure 1: Examples captured from natural scenes.