BMND: Direct Poisson Denoising by N-Dimensional Block Matching and Collaborative Filtering
Poisson denoising of scientific data requires methods that account for signal-dependent noise while accommodating different data dimensionalities and preserving quantitative intensity information. We present BMND, a dimension-independent extension of block matching and collaborative filtering for Gaussian and Poisson o...