Hardware-Oriented Shallow Joint Demosaicing and Denoising
Yang Xiao-dong, Wengang Zhou, Houqiang Li · 2022 IEEE International Conference on Image Processing (ICIP) · 2022
Demosaicing and denoising are two important procedures in image signal processing. Although they can be performed separately, the better approach is to perform demosaicing and denoising jointly. From traditional methods to deep learning methods, many joint demosaicing and denoising algorithms are available, but few of them can achieve good image quality while maintaining a low cost. In this paper, we propose a new high-quality, low-cost, and hardware-oriented joint demosaicing and denoising algorithm. First, we introduce an efficient interpolation-based demosaicing algorithm. Then, we develop a new edge-preserving wavelet denoising algorithm with a novel voting-based direction estimation method. Finally, we present our innovative joint demosaicing and denoising algorithm. Our method conducts demosaicing and denoising alternatively, sharing the same direction information. The obtained experimental results show that the new algorithm can achieve better performance with less than 1/40 of the processing time required by other traditional algorithms.