By Topic

A Tour of Modern Image Filtering: New Insights and Methods, Both Practical and Theoretical

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
Peyman Milanfar ; University of California, Santa Cruz, California 95064 USA

In this article, the author presents a practical and accessible framework to understand some of the basic underpinnings of these methods, with the intention of leading the reader to a broad understanding of how they interrelate. The author also illustrates connections between these techniques and more classical (empirical) Bayesian approaches. The proposed framework is used to arrive at new insights and methods, both practical and theoretical. In particular, several novel optimality properties of algorithms in wide use such as block-matching and three-dimensional (3-D) filtering (BM3D), and methods for their iterative improvement (or nonexistence thereof) are discussed. A general approach is laid out to enable the performance analysis and subsequent improvement of many existing filtering algorithms. While much of the material discussed is applicable to the wider class of linear degradation models beyond noise (e.g., blur,) to keep matters focused, we consider the problem of denoising here.

Published in:

IEEE Signal Processing Magazine  (Volume:30 ,  Issue: 1 )