Adaptive Multispectral Encoding Network for Image Demoiréing
Qiang G. Dai, Xi Cheng, Li Zhang, Le-Kang Sun · IEEE Transactions on Instrumentation and Measurement · 2023
Moiré often appears when photographing textured objects, which can seriously degrade the quality of captured photos. Due to the wide distribution of moiré and the dynamic properties of moiré, it is a challenge to effectively remove moiré patterns. For this purpose, we present an adaptive multi-spectral encoding network (AMSDM) for image demoiréing. In AMSDM, we leverage a multiscale network structure to process moiré images at different spatial resolutions, which can relieve the issue of moiré with distributed frequency spectrum. To solve the issue of dynamic properties of moiré, we design an adaptive multi-spectral encoding (AMSE) module to encode moiré patterns adaptively, which helps AMSDM restore moiré images clearly. Besides, a demoiréing convolutional network block (DMCNB) in the AMSE module makes AMSDM have the adaptability and the long-range correlation; thus, it can learn both global and local information about moiré images. Extensive experimental results indicate that our proposed AMSDM significantly outperforms state-of-the-art methods and achieves a great balance between performance and efficiency.