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Proceedings Paper • Open Access

Data-adaptive filtering and the state of the art in image processing (Presentation Video)
Author(s): Peyman Milanfar

Paper Abstract

The most effective recent approaches to processing and restoration of images and video are ones that flexibly adapt themselves to the content of these signals. These high performance methods have come about through the convergence of several powerful ideas from different science and engineering disciplines. Examples include Moving Least Square (from computer graphics), the Bilateral Filter and Anisotropic Diffusion (from computer vision), Boosting and Spectral Methods (from Machine Learning), Non-local Means and Bregman Iterations (from Applied Math), Kernel Regression and Iterative Scaling (from Statistics). These approaches are deeply connected; and in this talk, I will present a framework for understanding many common underpinnings of these ideas. This has led us to new insights and algorithms, yielding both deeper theoretical analysis, and state of the art results in practice.

Paper Details

Date Published: 19 September 2014
PDF: 1 pages
Proc. SPIE 9216, Optics and Photonics for Information Processing VIII, 92160Q (19 September 2014); doi: 10.1117/12.2063108
Show Author Affiliations
Peyman Milanfar, Univ. of California, Santa Cruz (United States)

Published in SPIE Proceedings Vol. 9216:
Optics and Photonics for Information Processing VIII
Abdul A. S. Awwal; Khan M. Iftekharuddin; Mohammad A. Matin; Andrés Márquez, Editor(s)

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