Reference : Patch-based Statistical Performance Analysis of Upsampling for Precise Super–Resolution
Scientific congresses, symposiums and conference proceedings : Paper published in a book
Engineering, computing & technology : Computer science
http://hdl.handle.net/10993/20838
Patch-based Statistical Performance Analysis of Upsampling for Precise Super–Resolution
English
Aouada, Djamila mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Al Ismaeil, Kassem mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Ottersten, Björn mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Mar-2015
11th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISAPP'15)
Yes
No
International
11th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISAPP)
from 27-3-2015 to 29-03-2015
[en] Super-resolution ; affine bias model ; patch-based
[en] 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. This 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.
Fonds National de la Recherche - FnR
I2R-DIR-PFN-11FAVE > C11/IS/1204105 : FAVE > 01/01/2012 - 31/12/2014 > OTTERSTEN Björn
Researchers
http://hdl.handle.net/10993/20838

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