Section: New Software and Platforms
ND-SAFIR
Keywords: Biology - Health - Image analysis - Photonic imaging - Fluorescence microscopy - Biomedical imaging
Scientific Description: The ND-Safir software removes additive Gaussian and non-Gaussian noise in still 2D or 3D images or in 2D or 3D image sequences (without any motion computation) [5]. The method is unsupervised and is based on a pointwise selection of small image patches of fixed size (a data-driven adapted way) in spatial or space-time neighbourhood of each pixel (or voxel). The main idea is to modify each pixel (or voxel) using the weighted sum of intensities within an adaptive 2D or 3D (or 2D or 3D + time) neighbourhood and to use image patches to take into account complex spatial interactions. The neighbourhood size is selected at each spatial or space-time position according to a bias-variance criterion. The algorithm requires no tuning of control parameters (already calibrated with statistical arguments) and no library of image patches. The method has been applied to real noisy images (old photographs, jpeg -coded images, videos, ...) and is exploited in different biomedical application domains (time-lapse fluorescence microscopy, video-microscopy, mri imagery, x -ray imagery, ultrasound imagery, ...).
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Participants: Jérôme Boulanger, Charles Kervrann, Patrick Bouthemy, Jean Salamero.
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APP deposit number: IDDN.FR.001.190033.002.S.A.2007.000.21000 / new release 3.0 in 2013)
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Free academic software distribution: Binaries of the software ND-safir are freely and electronically distributed (http://serpico.rennes.inria.fr/doku.php?id=software:nd-safir:index).
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On-line demo: http://mobyle-serpico.rennes.inria.fr/cgi-bin/portal.py#forms::NDSafir
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Languages: C/C++, Matlab and Java (plug-in ImageJ : http://rsbweb.nih.gov/ij/). The C/C++ software has been developed under Linux using the CImg library and has been tested over several platforms such as Linux/Unix, Windows XP and Mac OS.
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Commercial licence agreements: Innopsys, Roper Scientfic, Photmetrics, Nikon Europe BV (2016).
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Reference: [5]