Image denoising by multiple Compressed Sensing reconstructions

Abstract : 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 sparsity 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.