Patch-Based Nonlocal Functional for Denoising Fluorescence Microscopy Image Sequences
By Jérôme Boulanger, Charles Kervrann, Patrick Bouthemy, Peter Elbau, Jean-Baptiste Sibarita, Jean Salamero. IEEE Transactions on Medical Imaging, 2010
303 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition, Media Technology
View Paper: https://www.semanticscholar.org/paper/fa23031d601678b001aaa62e41f7fb34afe60f4a
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Vision and Pattern Recognition
- Michel Grédiac
- Joseph Salmon
- Rebecca M. Willett
- Frédéric Sur
- Charles-Alban Deledalle
- Zachary T. Harmany
- Benoît Blaysat
- Fabrice Pierron
In Media Technology
- Michel Grédiac
- Joseph Salmon
- Rebecca M. Willett
- Frédéric Sur
- Charles-Alban Deledalle
- Zachary T. Harmany
- Benoît Blaysat
Citations in the corpus
- Poisson Noise Reduction with Non-local PCA (2012, methodology): “In terms of PSNR, defined in the classical way (for 8-bit images) PSNR(f̂ , f) = 10 log10 2552 1 M ∑ i (f̂i − fi)2 , (20) our method globally improves upon other state-of-theart methods such as Poisson-NLM [14], SAFIR [5], and Poisson Multiscale Partitioning (PMP) [42] for the very low light levels ”
- The Grid Method for In‐plane Displacement and Strain Measurement: A Review and Analysis (2016, background): “This is however a rough assumption since actual camera sensor noise is Poisson-Gaussian and heteroscedastic (or signaldependent): the higher the brightness, the higher the noise level [185], and noise variance in images may reasonably be modeled with an affine function of the grey level [186, 187, 1”