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Title: Featured-based algorithm for the automated registration of multisensorial/multitemporal oceanographic satellite imagery
Authors: Eugenio González, Francisco 
Marcello, Javier 
UNESCO Clasification: 220990 Tratamiento digital. Imágenes
Keywords: Image Registration
Feature Detection
Contour Matching
Optimization Approach
Multitemporal And Multisensorial Images
Issue Date: 2009
Project: Esp2005-06823-C05-04 Calibración de Las Medidas Obtenidas Por El Radiometro Miras de la Mision Smos y Generacion de Mapas de Salinidad y Humedad Del Suelo. Parte Ulpgc 
Journal: Algorithms 
Abstract: Spatial registration of multidate or multisensorial images is required for many applications in remote sensing. Automatic image registration, which has been extensively studied in other areas of image processing, is still a complex problem in the framework of remote sensing. In this work we explore an alternative strategy for a fully automatic and operational registration system capable of registering multitemporal and multisensorial remote sensing satellite images with high accuracy and avoiding the use of ground control points, exploiting the maximum reliable information in both images (coastlines not occluded by clouds), which have been coarsely geometrically corrected only using an orbital prediction model. The automatic feature-based approach is summarized as follows: i) Reference image coastline extraction; ii) Sensed image gradient energy map estimation and iii) Contour matching, mapping function estimation and transformation of the sensed images. Several experimental results for single sensor imagery (AVHRR/3) and multisensorial imagery (AVHRR/3-SeaWiFS-MODIS-ATSR) from different viewpoints and dates have verified the robustness and accuracy of the proposed automatic registration algorithm, demonstrating its capability of registering satellite images of coastal areas within one pixel. © 2009 by the authors.
ISSN: 1999-4893
DOI: 10.3390/a2031087
Source: Algorithms[ISSN 1999-4893],v. 2 (3), p. 1087-1104
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