Adaptive Video Demoiréing Network With Subtraction-Guided Alignment

In this letter, we propose an adaptive video demoiréing network (AVDNet), which dynamically suppresses moiré patterns in video environments by leveraging both the spectral and temporal characteristics of moiré artifacts. It consists of two key modules: the adaptive bandpass block (ABB) and the subtraction-guided alignment block (SGAB). ABB performs frame-wise demoiréing in the implicit frequency domain using an adaptive bandpass filter that modulates its response to match the moiré spectral characteristics of each frame. SGAB exploits subtraction maps between adjacent frames to guide alignment and suppress the temporal propagation of moiré artifacts. Experimental results demonstrate that AVDNet outperforms state-of-the-art methods quantitatively and qualitatively while maintaining a compact model size and low computational cost.