Publication:
Estimation of the Regularisation Parameter in Huber-MRF for Image Resolution Enhancement

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Date

2013

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Springer

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Abstract

The Huber Markov Random Field (H-MRF) has been proposed for image resolution enhancement as a preferable alternative to Gaussian Random Markov Fields (G-MRF) for its ability to preserve discontinuities in the image. However, its performance relies on a good choice of a regularisation parameter. While automating this choice has been successfully tackled for G-MRF, the more sophisticated form of H-MRF makes this problem less straightforward. In this paper we develop an approximate solution to this problem, by upper-bounding the partition function of the H-MRF. We demonstrate the working and flexibility of our approach in image super-resolution experiments.

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Keywords

Huber prior, Hyper-parameter Optimisation, Super-resolution

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