Suyash P. Awate Suyash P. Awate
Associate Professor
Computer Science and Engineering Department, Indian Institute of Technology (IIT) Bombay
Office: A-214, Kanwal Rekhi Building
Email: my-first-name @cse.iitb.ac.in
   
Research Publications Teaching Students CV Personal
 
Nonparametric Empirical-Bayes Approach for Patch-Based MRI Denoising
 
Suyash P. Awate, Ross T. Whitaker
Feature-Preserving MRI Denoising: A Nonparametric Empirical Bayes Approach
IEEE Trans. Med. Imaging 2007, 26(9):1242-1255
 
Bayesian Image Denoising: A Key Problem
(1) How to model the prior (i.e. Markov statistics of noiseless signal) ?
(2) How to estimate the prior ?
 
Challenges Using Pre-Tuned Parametric Priors
(1) Strong models on signal
(2) Parameters of the model tuned (incorrectly) by hand or via training
 
Key Idea : Nonparametric Empirical-Bayes Estimation
(1) Model the prior, i.e. Markov statistics of the noiseless signal, using nonparametric statistical schemes
(2) Estimate the prior from the image that is to be denoised, knowing the noise model
(3) Use this estimate of the prior for optimal Bayesian denoising

Estimating the Prior
 
Bayesian Denoising by Iterated Conditional Entropy Reduction (ICER)

 
Denoised Images


Residual Images = difference between denoised image and noiseless image
 
Validation : Quantitative (BrainWeb repository)

 
Denoised a Real MR Image

 
Related Works
 
Peyman Milanfar
A Tour of Modern Image Filtering: New Insights and Methods, Both Practical and Theoretical
IEEE Signal Process. Mag. 30(1): 106-128 (2013)
 
Iterative Nonlocal Means, or UINTA

Suyash P. Awate, Ross T. Whitaker
Unsupervised, Information-Theoretic, Adaptive Image Filtering with Applications to Image Restoration
IEEE Trans. Pattern Analysis & Machine Intelligence (TPAMI) 2006, Vol. 28, Num. 3 , pp. 364-376

Suyash P. Awate, Ross T. Whitaker
Higher-Order Image Statistics for Unsupervised, Information-Theoretic, Adaptive Image Filtering
IEEE Computer Vision & Pattern Recognition (CVPR), June 2005, vol 2, pp 44-51
 
T. Weissman, E. Ordentlich, G. Seroussi, S. Verdu, and M. Weinberger
Universal discrete denoising: Known channel
IEEE Trans. Information Theory 2005, 51(1):5-28 DUDE and Extensions
 
H. Robbins
The empirical Bayes approach to statistical decision problems
Annals of Mathematical Statistics 1964, 35(1):1-20
 
H. Robbins
An empirical Bayes approach to statistics
In Proc. Third Berkeley Symp. Math. Stat. Prob. 1964, pp.157-164