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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 Ga
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