MMSE Estimation for Poisson Noise Removal in Images
This work addresses noise suppression in medical imaging, microscopy, and astronomy, but appears incremental as it builds on existing MMSE and neighbor search techniques.
The authors tackled Poisson noise removal in images by proposing a patch-wise strategy using an MMSE estimator, achieving results that are preferable for low signal-to-noise ratios.
Poisson noise suppression is an important preprocessing step in several applications, such as medical imaging, microscopy, and astronomical imaging. In this work, we propose a novel patch-wise Poisson noise removal strategy, in which the MMSE estimator is utilized in order to produce the denoising result for each image patch. Fast and accurate computation of the MMSE estimator is carried out using k-d tree search followed by search in the K-nearest neighbor graph. Our experiments show that the proposed method is the preferable choice for low signal-to-noise ratios.