Affine invariant total variation models

Authors:
Alexander Balinsky;Helen Balinsky
Affiliations:
Cardiff University, Cardiff, United Kingdom;Hewlett-Packard Laboratories, Bristol, United Kingdom
Venue:
CGIM '08 Proceedings of the Tenth IASTED International Conference on Computer Graphics and Imaging
Year:
2008

Citing 2
Cited 0

Nonlinear total variation based noise removal algorithms

Proceedings of the eleventh annual international conference of the Center for Nonlinear Studies on Experimental mathematics : computational issues in nonlinear science: computational issues in nonlinear science
Image Processing And Analysis: Variational, Pde, Wavelet, And Stochastic Methods

Image Processing And Analysis: Variational, Pde, Wavelet, And Stochastic Methods

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Abstract

Since their introduction in a classical paper by Rudin, Osher and Fatemi [2], total variation minimizing models have become one of the most popular and successful tools for image restoration. Unfortunately, the total variation functional is not invariant under general affine transformation. Invariance under affine transformation is very important for many image processing tasks. In this paper we introduce a new affine invariant regularization functional which has many properties similar to total variation and can be used for affine invariant denoising and restoration tasks.