Adaptive regularization for multiple image restoration using an extended total variations approach

Authors

Matthew Kitchener, University of WollongongFollow
Abdesselam Bouzerdoum, University of WollongongFollow
Son Lam Phung, University of WollongongFollow

RIS ID

50705

Publication Details

Kitchener, M. Andrew., Bouzerdoum, A. & Phung, S. (2011). Adaptive regularization for multiple image restoration using an extended total variations approach. 2011 18th IEEE International Conference on Image Processing, ICIP 2011 (pp. 697-700). USA: IEEE.

Abstract

In this paper a Variational Inequality method for multiple in- put, multiple output image restoration is presented using an extended Total Variations (TV) regularizer. This approach calculates an adaptive regularization parameter for each image based on their respective degradations. The proposed ex- tended Total Variations regularizer combines both intra-image and inter-image pixel information for improved restoration performance. Hyperparameters for controlling this new TV measure are calculated using a Bayesian joint maximum a posteriori approach.