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Improving the robustness of least squares template matching with a line-search algorithm
Umeå University, Faculty of Science and Technology, Department of Computing Science.ORCID iD: 0000-0002-7657-6917
2002 (English)In: Close-range imaging, long-range vision: proceedings of the Commission V symposium, ISPRS , 2002, Vol. 34, no 5, 7-11 p.Conference paper (Other academic)
Abstract [en]

The Adaptive Least Squares Matching (ALSM) problem of Gruen is conventionally described as a statistical estimation problem. This paper shows that the ALSM problem may also be interpreted as a weighted non-linear least squares problem. This enables optimization theory to be applied to the ALSM problem. The ALSM algorithm may be interpreted as an instance of the well-known Gauss-Newton algorithm. A problem-independent termination criteria is introduces based on angles in high-dimensional vector spaces. The line-search modification of the Gauss-Newton method is explained and applied to the ALSM problem. The implications of the line-search modification is an increased robustness, reduced oscillations, and increased pull-in range. A potential drawback is the increased number of convergences toward side minima in images with repeating patterns.

Place, publisher, year, edition, pages
ISPRS , 2002. Vol. 34, no 5, 7-11 p.
, ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, ISSN 1682-1750 ; Vol 34 part 5
Keyword [en]
algorithms, matching, digital, reliability, targets, non-linear optimization
URN: urn:nbn:se:umu:diva-40121OAI: diva2:397996
Commission V Symposium "Close-Range Imaging, Long-Range Vision", 2-6 Sept., Corfu, Greece
Available from: 2011-02-18 Created: 2011-02-16 Last updated: 2014-06-11Bibliographically approved

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Börlin, Niclas
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