SAFIR-nD - image denoising software
Participant : Charles Kervrann.
The safir -nd software written in c ++, java and matlab , enables to remove additive Gaussian and non-Gaussian noise in a still 2d or 3d image or in a 2d or 3d image sequence (with no motion computation). The method is unsupervised. It is based on a pointwise selection of small image patches of fixed size in (a data-driven adapted) spatial or space-time neighborhood of each pixel (or voxel). The main idea is to associate with each pixel (or voxel) the weighted sum of intensities within an adaptive 2d or 3d (or 2d or 3d + time) neighborhood and to use image patches to take into account complex spatial interactions. The neighborhood 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 (fluorescence microscopy, video-microscopy, mri imagery, x -ray imagery, ultrasound imagery, ...). This algorithm outperforms most of the best published denoising methods for still images or image sequences.