DEEP RESIDUAL NETWORK FOR COLOR FILTER ARRAY IMAGE DENOISING

摘要

A deep residual network dedicated to color filter array mosaic pattern is disclosed. A mosaic stride convolution layer is introduced to match the mosaic pattern of a multispectral filter arrays (MSFA) or a color filter array raw image. A data augmentation using MSFA shifting and dynamic noise are applied to make the model robust to different noise levels. Network optimization criteria may be created by using the noise standard deviation to normalize the L ¹ loss function. Comprehensive experiments demonstrates that the disclosed deep residual network outperform the state-of-the-art denoising algorithms in MSFA field.