Software

There are numerous ways to denoise and image, and the most effective methods are nowadays based on deep learning and supervised training. This work of ours (with Grisha Vaksman and Peyman Milanfar) proposes a specific architecture that resembles BM3D with several added values. An interesting twist in our work is the ability to take the universally trained network and adapt it to an incoming image, boosting this way the denoising performance quite substantially.