Plug and Play Software

Plug-and-play (P&P) priors is an algorithmic method that allows denoising operators to be used as prior models in regularized Bayesian inversion. More generally, it is a modular method for fusing information from multiple sources in reconstruction problems.

The following downloadable matlab software package implements P&P for some simple problems such as super resolution and sparse inpainting using prior models based on denoising algorithms such as BM3D and non-local means (NLM) denoising. - Directory containing Matlab implementation of Plug and Play to super resolution and sparse inpainting.

Relevant Papers:
paper Singanallur V. Venkatakrishanan, Charles A. Bouman, and Brendt Wohlberg, ``Plug-and-Play Priors for Model Based Reconstruction,'' IEEE 2013 Global Conference on Signal and Information Processing (GlobalSIP), Austin, Texas, USA, December 3-5, 2013.

paper Suhas Sreehari, S. Venkat Venkatakrishnan, Brendt Wohlberg, Gregery T. Buzzard, Lawrence F. Drummy, Jeffrey P. Simmons, and Charles A. Bouman, ``Plug-and-Play Priors for Bright Field Electron Tomography and Sparse Interpolation,'' IEEE Transactions on Computational Imaging, vol. 2, no. 4, Dec. 2016.

paper Suhas Sreehari, S. V. Venkatakrishnan, Katherine L. Bouman, Jeffrey P. Simmons, Lawrence F. Drummy, and Charles A. Bouman ``Muti-Resolution Data Fusion for Super-Resolution Electron Microscopy,'' NTIRE 2017 at CVPR 2017.

For more information, contact:
Charles A. Bouman
School of Electrical and Computer Engineering
Purdue University
West Lafayette, IN 47907-1285