Bayram, I.Guerquin-Kern, M.Terres-Cristofani, R.Unser, M.2011-12-162011-12-162011-12-16201010.1109/ICIP.2010.5652743https://infoscience.epfl.ch/handle/20.500.14299/74724WOS:000287728000143Modern deconvolution algorithms are often specified as minimization problems involving a non-quadratic regularization functional. When the latter is a wavelet-domain l(1)-norm that favors sparse solutions, the problem can be solved by a simple iterative shrinkage/thresholding algorithm (ISTA). This approach provides state-of-the-art results in 2-D, but is harder to deploy in 3-D because of its slow convergence.fluorescent microscopydeconvolutionwavelet regularizationaccelerated shrinkage/thresholdingLinear Inverse ProblemsThresholding AlgorithmImage-Restorationtext::conference output::conference proceedings::conference paper