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Depth super-resolution by enhanced shift and add
Interdisciplinary Centre for Security, Reliability and Trust, Universtity of Luxembourg, Luxembourg.ORCID iD: 0000-0003-2298-6774
2013 (English)In: Computer Analysis of Images and Patterns: 15th International Conference, CAIP 2013, York, UK, August 27-29, 2013, Proceedings, Part II, Springer, 2013, Vol. 8048 LNCS, no PART 2, 100-107 p.Conference paper (Refereed)
Abstract [en]

We use multi-frame super-resolution, specifically, Shift & Add, to increase the resolution of depth data. In order to be able to deploy such a framework in practice, without requiring a very high number of observed low resolution frames, we improve the initial estimation of the high resolution frame. To that end, we propose a new data model that leads to a median estimation from densely upsampled low resolution frames. We show that this new formulation solves the problem of undefined pixels and further allows to improve the performance of pyramidal motion estimation in the context of super-resolution without additional computational cost. As a consequence, it increases the motion diversity within a small number of observed frames, making the enhancement of depth data more practical. Quantitative experiments run on the Middlebury dataset show that our method outperforms state-of-the-art techniques in terms of accuracy and robustness to the number of frames and to the noise level.

Place, publisher, year, edition, pages
Springer, 2013. Vol. 8048 LNCS, no PART 2, 100-107 p.
, Lecture Notes in Computer Science, ISSN 0302-9743 ; 8048
Keyword [en]
Dense upsampling, Motion diversity, Pyramidal optical flow, Super-resolution, Time-of-flight depth data
National Category
Signal Processing
URN: urn:nbn:se:kth:diva-138998DOI: 10.1007/978-3-642-40246-3_13ScopusID: 2-s2.0-84884479378ISBN: 978-364240245-6OAI: diva2:682135
15th International Conference on Computer Analysis of Images and Patterns, CAIP 2013; York; United Kingdom; 27 August 2013 through 29 August 2013

QC 20140603

Available from: 2013-12-23 Created: 2013-12-23 Last updated: 2014-06-03Bibliographically approved

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Ottersten, Björn
Signal Processing

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