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Authors: Djamila Aouada ; Kassem Al Ismaeil and Björn Ottersten

Affiliation: University of Luxembourg, Luxembourg

ISBN: 978-989-758-089-5

Keyword(s): Super-resolution, Affine Bias Model, UP-SR, MSE, Depth Camera, Patch-based.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Image Enhancement and Restoration ; Image Formation and Preprocessing

Abstract: All existent methods for the statistical analysis of super–resolution approaches have stopped at the variance term, not accounting for the bias in the mean square error. In this paper we give an original derivation of the bias term. We propose to use a patch-based method inspired by the work of (Chatterjee and Milanfar, 2009). Our approach, however, is completely new as we derive a new affine bias model dedicated for the multi-frame super resolution framework. We apply the proposed statistical performance analysis to the Upsampling for Precise Super–Resolution (UP-SR) algorithm. This algorithm was shown experimentally to be a good solution for enhancing the resolution of depth sequences in both cases of global and local motions. Its performance is herein analyzed theoretically in terms of its approximated mean square error, using the proposed derivation of the bias. This analysis is validated experimentally on simulated static and dynamic depth sequences with a known ground truth. Thi s provides an insightful understanding of the effects of noise variance, number of observed low resolution frames, and super–resolution factor on the final and intermediate performance of UP–SR. Our conclusion is that increasing the number of frames should improve the performance while the error is increased due to local motions, and to the upsampling which is part of UP-SR. (More)

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Paper citation in several formats:
Aouada, D.; Al Ismaeil, K. and Ottersten, B. (2015). Patch-based Statistical Performance Analysis of Upsampling for Precise Super–Resolution.In Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2015) ISBN 978-989-758-089-5, pages 186-193. DOI: 10.5220/0005316001860193

@conference{visapp15,
author={Djamila Aouada. and Kassem Al Ismaeil. and Björn Ottersten.},
title={Patch-based Statistical Performance Analysis of Upsampling for Precise Super–Resolution},
booktitle={Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2015)},
year={2015},
pages={186-193},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005316001860193},
isbn={978-989-758-089-5},
}

TY - CONF

JO - Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2015)
TI - Patch-based Statistical Performance Analysis of Upsampling for Precise Super–Resolution
SN - 978-989-758-089-5
AU - Aouada, D.
AU - Al Ismaeil, K.
AU - Ottersten, B.
PY - 2015
SP - 186
EP - 193
DO - 10.5220/0005316001860193

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