Turbo denoising for mobile photographic applications
Tak-Shing Wong, Peyman Milanfar · 2016
We propose a new denoising algorithm for camera pipelines and other photographic applications. We aim for a scheme that is (1) fast enough to be practical even for mobile devices, and (2) handles the realistic content dependent noise in real camera captures. Our scheme consists of a simple two-stage non-linear processing. We introduce a new form of boosting/blending which proves to be very effective in restoring the details lost in the first denoising stage. We also employ IIR filtering to significantly reduce the computation time. Further, we incorporate a novel noise model to address the content dependent noise. For realistic camera noise, our results are competitive with BM3D, but with nearly 400 times speedup.