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Proceedings Paper

Registration of satellite imagery utilizing the low-low components of the wavelet transform
Author(s): Emre Kaymaz; Bao-Ting Lerner; William J. Campbell; Jacqueline Le Moigne; John F. Pierce
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Paper Abstract

The need for fast, accurate, and reliable image registration techniques is increasing primarily due to the large amount of remote sensing data which will be generated by future Earth and space missions and the diversity of such data in temporal, spatial and spectral components. Registration of the remote sensing imagery is one of the most important steps in view of further processing and interpretation of such data since the information fusion from multiple sensors start with the registration of the data. Traditional approaches to image registration require substantial human involvement in the selection and matching of the ground control points in the reference and input data sets. Considering the dramatic increase that is predicted in the volume of remote sensing data that will be collected during future missions, it is imperative that fully automatic registration algorithms be utilized. We present a three-step approach to automatic registration of remote sensing imagery. The first step involves the wavelet decomposition of the reference and input images to be registered. In the second step, we extract domain independent features to be used as the control points from the low-low components of the wavelet decompositions of the reference and input images employing the Lerner algebraic edge detector (LAED) and the Sobel edge detector. Finally, we utilize the maxima of the low-low wavelet coefficients preprocessed by the edge detectors and an exclusive-or based similarity metric to compute the transformation function. We illustrate the effectiveness of the proposed registration method on a Landsat thematic mapper image of the Pacific Northwest, and show that the performance of the LAED is superior to that of the Sobel edge detector.

Paper Details

Date Published: 26 February 1997
PDF: 10 pages
Proc. SPIE 2962, 25th AIPR Workshop: Emerging Applications of Computer Vision, (26 February 1997); doi: 10.1117/12.267838
Show Author Affiliations
Emre Kaymaz, KT-Tech, Inc. (United States)
Bao-Ting Lerner, KT-Tech, Inc. (United States)
William J. Campbell, NASA Goddard Space Flight Ctr. (United States)
Jacqueline Le Moigne, NASA Goddard Space Flight Ctr. (United States)
John F. Pierce, U.S. Naval Academy (United States)

Published in SPIE Proceedings Vol. 2962:
25th AIPR Workshop: Emerging Applications of Computer Vision
David H. Schaefer; Elmer F. Williams, Editor(s)

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