BMND: Direct Poisson Denoising by N-Dimensional Block Matching and Collaborative Filtering

arXiv:2609.34622 · cs.CV · Submitted 2026-09-28 · Read on arXiv

cs.CV

Submitted: 2026-09-28

Updated: 2026-09-28

Code: https://github.com/cduhme/bmnd

Terminology

Aggregation — 67× in this paper · explained in 1 episode
Calibration — 20× in this paper · explained in 7 episodes
Ablation — 9× in this paper · explained in 1 episode
Covariance Propagation — 7× in this paper · explained in 2 episodes
Benchmark — 4× in this paper · explained in 2 episodes
Reconstruction Error — 4× in this paper · explained in 2 episodes
Trace — 4× in this paper · explained in 2 episodes
Ablation study — 3× in this paper · explained in 1 episode
Adaptation — 3× in this paper · explained in 1 episode
Accuracy — 2× in this paper · explained in 1 episode
Conference on Computer Vision and Pattern Recognition — 2× in this paper
Core — 2× in this paper · explained in 2 episodes
Inverse Problem — 2× in this paper · explained in 2 episodes
Wavelet Transform — 2× in this paper · explained in 2 episodes
Alignment — 1× in this paper · explained in 1 episode
Consistency — 1× in this paper · explained in 3 episodes
Fidelity — 1× in this paper · explained in 2 episodes
Fluorescence Microscopy Denoising — 1× in this paper
Interpretability — 1× in this paper · explained in 15 episodes
Redundancy — 1× in this paper · explained in 2 episodes
Robustness — 1× in this paper · explained in 5 episodes
Signal-to-noise ratio (SNR) — 1× in this paper · explained in 2 episodes

Sources

Noise2Noise: Learning Image Restoration without Clean Data

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