DEEP RESIDUAL NETWORK FOR COLOR FILTER ARRAY IMAGE DENOISING

摘要

Described herein are embodiments of a deep residual network dedicated to color filter array mosaic patterns. 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. Embodiments of a data augmentation using MSFA shifting and dynamic noise are applied to make the model robust to different noise levels. Embodiments of network optimization criteria may be created by using the noise standard deviation to normalize the L1 loss function. Comprehensive experiments demonstrate that embodiments of the disclosed deep residual network outperform the state-of-the-art denoising algorithms in MSFA field.