------------------------------------------------------------------ demo software for iterative VST-based Poisson image deblurring Public release v1.0 (18 April 2017) ------------------------------------------------------------------ Copyright (c) 2017 Tampere University of Technology. All rights reserved. This work should be used only for nonprofit purposes. Authors: Lucio Azzari Alessandro Foi Web page: http://www.cs.tut.fi/~foi/invansc/ ------------------------------------------------------------------ Installation and requirements ------------------------------------------------------------------ This software is designed to run on *) MS Windows, Linux, or Mac OSX (32-bit or 64-bit CPU) *) Matlab v.7 or later It requires: * Exact unbiased inverse package "invansc" http://www.cs.tut.fi/~foi/invansc/ * BM3D denoising filter http://www.cs.tut.fi/~foi/GCF-BM3D/ The demo script uses also: * Statistics Toolbox (to generate Poisson data "poissrnd"), * Image Processing Toolbox (only for visualization with "imshow"). ------------------------------------------------------------------ Content ------------------------------------------------------------------ demo_iterVSTpoissonDeb.m demo script iterVSTpoissonDeb.m main deblurring function bin_B_h.m binning function debin_Binv_h.m debinning function paramsFromQstdFunDeb.mat function handles to set parameters BM3D_COL.m basic BM3D for correlated noise based on deconvolution function from [2] demo_ISBI2017_Table1.m demo reproducing Table 1 in [1] images_ISBI (folder) test images used for [1] ------------------------------------------------------------------ Reference ------------------------------------------------------------------ [1] L. Azzari and A. Foi, "Variance Stabilization in Poisson Image Deblurring", Proc. IEEE ISBI 2017 [2] K. Dabov, A. Foi, V. Katkovnik, and K. Egiazarian, "Image restoration by sparse 3D transform-domain collaborative filtering," Proc. SPIE Electronic Imaging '08, vol. 6812, no. 681207, San Jose (CA), USA, January 2008. http://doi.org/10.1117/12.766355 ------------------------------------------------------------------ Disclaimer ------------------------------------------------------------------ Any unauthorized use of these routines for industrial or profit- oriented activities is expressively prohibited. By downloading and/or using any of these files, you implicitly agree to all the terms of the TUT limited license: http://www.cs.tut.fi/~foi/invansc/legal_notice.html