Mop Moiré Patterns Using MopNet

Moiré pattern is a common image quality degradation caused by frequency aliasing between monitors and cameras when taking screen-shot photos. The complex frequency distribution , imbalanced magnitude in colour channels , and diverse appearance attributes of moiré pattern make its removal a challenging problem. In this paper, we propose a Moiré pattern Removal Neural Network (Mop-Net) to solve this problem. All core components of Mop-Net are specially designed for unique properties of moiré patterns, including the multi-scale feature aggregation to address complex frequency, the channel-wise target edge predictor to exploit imbalanced magnitude among colour channels, and the attribute-aware classifiers to characterize the diverse appearance for better modelling Moiré patterns. Quantitative and qualitative comparison experiments have validated the state-of-the-art performance of MopNet.