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26 February 1997 Registration of satellite imagery utilizing the low-low components of the wavelet transform
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Proceedings Volume 2962, 25th AIPR Workshop: Emerging Applications of Computer Vision; (1997) https://doi.org/10.1117/12.267838
Event: 25th Annual AIPR Workshop on Emerging Applications of Computer Vision, 1996, Washington, DC, United States
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.
© (1997) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Emre Kaymaz, Bao-Ting Lerner, William J. Campbell, Jacqueline Le Moigne, and John F. Pierce "Registration of satellite imagery utilizing the low-low components of the wavelet transform", Proc. SPIE 2962, 25th AIPR Workshop: Emerging Applications of Computer Vision, (26 February 1997); https://doi.org/10.1117/12.267838
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