Blind restoration of very-high-ISO photos via low-rank methods

We propose a new algorithm for blind restoration of very-high-ISO photos. Unlike previous methods that sequentially tackle the problem of noise estimation and image denoising, our approach alternatively refines the estimates of latent image and noise level function (NLF). We rigorously show how the existing low-rank based modeling of image prior can be extended to incorporate spatially inhomogeneous and signal-dependent noise. We develop a generalization of singular-value thresholding technique by making the thresh-old/regularization parameter doubly adaptive - adaptive to both local signal and noise variance estimates. Our experimental results have shown that the proposed auto-denoising algorithm is capable of achieving visually pleasant restoration of photos with ISO settings of above 6400 for a wide range of brand cameras and at a moderate computational cost.