Image denoising by multiple compressed sensing reconstructions
W Meiniel, Y Le Montagner, E Angelini… - 2015 IEEE 12th …, 2015 - ieeexplore.ieee.org
2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI), 2015•ieeexplore.ieee.org
In this paper, compressed sensing (CS) is investigated as a denoising tool in bioimaging.
Multiple reconstructions at low sampling rates are combined to generate high quality
denoised images using total-variation spar-sity constraints. The validity of the proposed
method is first assessed on a synthetic image with a known ground truth and then applied to
real biological images.
Multiple reconstructions at low sampling rates are combined to generate high quality
denoised images using total-variation spar-sity constraints. The validity of the proposed
method is first assessed on a synthetic image with a known ground truth and then applied to
real biological images.
In this paper, compressed sensing (CS) is investigated as a denoising tool in bioimaging. Multiple reconstructions at low sampling rates are combined to generate high quality denoised images using total-variation spar-sity constraints. The validity of the proposed method is first assessed on a synthetic image with a known ground truth and then applied to real biological images.
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