Monte Carlo Non-Local Means: Random Sampling for Large-Scale Image Filtering

We propose a randomized version of the nonlocal means (NLM) algorithm for large-scale image filtering. The new algorithm, called Monte Carlo nonlocal means (MCNLM), speeds up the classical NLM by computing a small subset of image patch distances, which are randomly selected according to a designed s...

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Veröffentlicht in:	IEEE transactions on image processing 2014-08, Vol.23 (8), p.3711-3725
Hauptverfasser:	Chan, Stanley H., Zickler, Todd, Lu, Yue M.
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithm design and analysis Algorithms Applied sciences Computational complexity Computer Simulation Detection, estimation, filtering, equalization, prediction Exact sciences and technology Filtering Filtration Image Enhancement - methods Image Interpretation, Computer-Assisted - methods Image processing Information, signal and communications theory Mathematical models Models, Statistical Monte Carlo Method Monte Carlo methods Noise measurement Noise reduction Numerical Analysis, Computer-Assisted Random variables Reproducibility of Results Sample Size Sampling Sensitivity and Specificity Signal and communications theory Signal processing Signal processing algorithms Signal Processing, Computer-Assisted Signal, noise Telecommunications and information theory
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