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Open AccessArticle

Optimizing SIFT for Matching of Short Wave Infrared and Visible Wavelength Images

Centre for Integrated Petroleum Research (Uni CIPR), P.O. Box 7810, N-5020 Bergen, Norway
Department of Informatics, University of Bergen, P.O. Box 7803, N-5020 Bergen, Norway
Author to whom correspondence should be addressed.
Remote Sens. 2013, 5(5), 2037-2056;
Received: 13 February 2013 / Revised: 12 April 2013 / Accepted: 15 April 2013 / Published: 24 April 2013
The scale invariant feature transform (SIFT) is a widely used interest operator for supporting tasks such as 3D matching, 3D scene reconstruction, panorama stitching, image registration and motion tracking. Although SIFT is reported to be robust to disparate radiometric and geometric conditions in visible light imagery, using the default input parameters does not yield satisfactory results when matching imagery acquired at non-overlapping wavelengths. In this paper, optimization of the SIFT parameters for matching multi-wavelength image sets is documented. In order to integrate hyperspectral panoramic images with reference imagery and 3D data, corresponding points were required between visible light and short wave infrared images, each acquired from a slightly different position and with different resolutions and geometric projections. The default SIFT parameters resulted in too few points being found, requiring the influence of five key parameters on the number of matched points to be explored using statistical techniques. Results are discussed for two geological datasets. Using the SIFT operator with optimized parameters and an additional outlier elimination method, allowed between four and 22 times more homologous points to be found with improved image point distributions, than using the default parameter values recommended in the literature. View Full-Text
Keywords: SIFT; optimization; SWIR; VIS; multi-wavelength; hyperspectral SIFT; optimization; SWIR; VIS; multi-wavelength; hyperspectral
MDPI and ACS Style

Sima, A.A.; Buckley, S.J. Optimizing SIFT for Matching of Short Wave Infrared and Visible Wavelength Images. Remote Sens. 2013, 5, 2037-2056.

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