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Remote Sens. 2017, 9(9), 965; doi:10.3390/rs9090965

Optimal Weight Design Approach for the Geometrically-Constrained Matching of Satellite Stereo Images

School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, 1439957131 Tehran, Iran
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Received: 13 June 2017 / Revised: 12 August 2017 / Accepted: 13 September 2017 / Published: 18 September 2017
(This article belongs to the Section Remote Sensing Image Processing)
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Abstract

This study presents an optimal weighting approach for combined image matching of high-resolution satellite stereo images (HRSI). When the rational polynomial coefficients (RPCs) for a pair of stereo images are available, some geometric constraints can be combined in image matching equations. Combining least squares image matching (LSM) equations with geometric constraints equations necessitates determining the appropriate weights for different types of observations. The common terms between the two sets of equations are the image coordinates of the corresponding points in the search image. Considering the fact that the RPCs of a stereo pair are produced in compliance with the coplanarity condition, geometric constraints are expected to play an important role in the image matching process. In this study, in order to control the impacts of the imposed constraint, optimal weights for observations were assigned through equalizing their average redundancy numbers. For a detailed assessment of the proposed approach, a pair of CARTOSAT-1 sub-images, along with their precise RPCs, were used. On top of obtaining different matching results, the dimension of the error ellipses of the intersection points in the object space were compared. It was shown through analysis that the geometric mean of the semi-minor and semi-major axis by our method was reduced 0.17 times relative to the unit weighting approach. View Full-Text
Keywords: constrained image matching; HRSI; weight design; RPC model constrained image matching; HRSI; weight design; RPC model
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Afsharnia, H.; Arefi, H.; Sharifi, M.A. Optimal Weight Design Approach for the Geometrically-Constrained Matching of Satellite Stereo Images. Remote Sens. 2017, 9, 965.

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