Radiographic Impulsive Noise removal (RaIN) filter - Matlab package for the Radiographic Impulsive Noise removal (RaIN) filter. Laboratory of Applied Intelligent Systems (AIS Lab) of the Computer Science Department University of Milan.
For references, see:
I. Frosio, S. Abati, N. A. Borghese, "Bayesian approach to impulsive noise removal in digital radiography," Int. Journal of CARS, Vol. 3, No. 1-2, Jun. 2008.
I. Frosio, N. A. Borghese, "Statistical Based Impulsive Noise Removal in Digital Radiography," IEEE Transactions on Medical Imaging, Vol.28, No.1, Jan. 2009, pp.3-16.
I. Frosio, M. Lucchese, N. A. Borghese, A new and reliable Poisson noise estimator for radiographic images, in Proc. ICIAP 2007, Modena (Italy), Sept. 2007.
Alternating Extragradient Method for Total Variation image restoration from Poisson data: the following zip file contains the Matlab M-function AEM.m implementing the AEM method, an M-file to use the function file for denoising and deblurring problems; some test problems are in folder Data. The code enables to reproduce some of the 2D numerical experiments in "An alternating extragradient method for total variation based image restoration from Poisson data", S. Bonettini, V. Ruggiero, Inverse Problems, Inverse Problems 27 (2011) 095001; doi: 10.1088/0266-5611/27/9/095001. The code enables to handle 3D restoration problems. The documentation of any M-file is reported in the comments.
AEM.zip (updated by A. Benfenati, S. Bonettini, V. Ruggiero on May 2018)
CLSRit: the following zip file contains the Matlab M-function CLSRit.m described in the paper: "An Iterative algorithm for large size
Least-Squares constrained regularization problems", E. Loli Piccolomini, F. Zama, Applied Mathematics and Computations, 217 (2011) 10343-10354. The folder contains also an execution example.
CLSRit.zip
SGP-dec: a Matlab package for the deconvolution of 2D and 3D images corrupted by Poisson noise. Following a maximum likelihood approach, SGP-dec computes a deconvolved image by early stopping the scaled gradient projection (SGP) algorithm for the solution of the optimization problem coming from the minimization of the generalized Kullback-Leibler divergence between the blurred image and the observed image.
For the SGP method, see the paper: A scaled gradient projection method for constrained image deblurring; S. Bonettini, R. Zanella, L. Zanni, Inverse Problems 25 (2009) 015002.
Documentation of the Matlab package (updated on Nov. 22, 2011): SGP-dec_doc.pdf
SGP-dec.tgz
For binary Linux library versions please contact the authors: riccardo.zanella@unife.it, luca.zanni@unimore.it, g.zanghirati@unife.it, roberto.cavicchioli@unimore.it
The following Matlab function implements the SGP method for n-dimensional object deblurring with the option of boundary effects removal. This is a preliminary version available for public download (see "Towards real-time image deconvolution applicatrion to confocal
and STED microscopy", R. Zanella et al., 2013, submitted to Scientific Reports.)
sgp_deblurring_boundary.zip
Similarity indexes: a Matlab package for computing similarity indexes. Laboratory of Applied Intelligent Systems (AIS Lab) of the Computer Science Department University of Milan.
The files ImageError.m and ImageErrorLoop.m are examples of usage.
For the index SSIM, see
Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli, "Image quality assessment: From error measurement to structural similarity"
IEEE Transactios on Image Processing, vol. 13, no. 4, Apr. 2004.
For the index FSIM, see
Lin Zhang, Lei Zhang, Xuanqin Mou, and David Zhang,"FSIM: a feature similarity index for image qualtiy assessment",IEEE Transactions on Image Processing 20(8): 2378-2386 (2011).
The routine ssim_index_true.m is implemented by Zhou Wang (Copyright(c) 2003).
The routine FSIM_index.m is implemented by Lin Zhang, Lei Zhang, Xuanqin Mou and David Zhang (Copyright(c) 2010) and modified by Mirko Lucchese for gray levels images with maximum gray level different from 255.
SimilarityIndexes.zip
Test-problems (Boccacci)
nebula
satellite
SGP-IDL: an Interactive Data Language (IDL) package for the single and multiple deconvolution of 2D images corrupted by Poisson noise, with the optional inclusion of a boundary effect correction. Following a maximum likelihood approach, SGP-IDL computes a deconvolved image by early stopping of the scaled gradient projection (SGP) algorithm for the solution of the optimization problem coming from the minimization of the generalized Kullback-Leibler divergence between the computed image and the observed image. The algorithms have been implemented also for Graphic Processing Units (GPUs).
Reference paper: Efficient deconvolution methods for astronomical imaging: algorithms and IDL-GPU codes. Prato M., Cavicchioli R., Zanni L., Boccacci P. and Bertero M., Astronomy & Astrophysics, in press.
Preprint available at the website
http://www.aanda.org/index.php?option=com_forthcoming&Itemid=18&lang=en_GB.utf8%2C+en_GB.UT#section_15
Documentation of the IDL package (updated on Dec. 14, 2011): SGP-IDL_dec.pdf
IDL routines: SGP-IDL.zip
AIRY - Astronomical Image Restoration in interferometrY
http://www.airyproject.eu/
