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F. Elaksher, A., A. Alharthy, A. (2008). SOLVING THE POINT CORRESPONDING PROBLEM BETWEEN MULTI RESOLUTION SATELLITE IMAGES USING A MODIFIED SVD-MATCHING ALGORITHM. JES. Journal of Engineering Sciences, 36(No 1), 27-37. doi: 10.21608/jesaun.2008.115585
Ahmed F. Elaksher; Abdullatif A. Alharthy. "SOLVING THE POINT CORRESPONDING PROBLEM BETWEEN MULTI RESOLUTION SATELLITE IMAGES USING A MODIFIED SVD-MATCHING ALGORITHM". JES. Journal of Engineering Sciences, 36, No 1, 2008, 27-37. doi: 10.21608/jesaun.2008.115585
F. Elaksher, A., A. Alharthy, A. (2008). 'SOLVING THE POINT CORRESPONDING PROBLEM BETWEEN MULTI RESOLUTION SATELLITE IMAGES USING A MODIFIED SVD-MATCHING ALGORITHM', JES. Journal of Engineering Sciences, 36(No 1), pp. 27-37. doi: 10.21608/jesaun.2008.115585
F. Elaksher, A., A. Alharthy, A. SOLVING THE POINT CORRESPONDING PROBLEM BETWEEN MULTI RESOLUTION SATELLITE IMAGES USING A MODIFIED SVD-MATCHING ALGORITHM. JES. Journal of Engineering Sciences, 2008; 36(No 1): 27-37. doi: 10.21608/jesaun.2008.115585

SOLVING THE POINT CORRESPONDING PROBLEM BETWEEN MULTI RESOLUTION SATELLITE IMAGES USING A MODIFIED SVD-MATCHING ALGORITHM

Article 3, Volume 36, No 1, January and February 2008, Page 27-37  XML PDF (616.38 K)
Document Type: Research Paper
DOI: 10.21608/jesaun.2008.115585
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Authors
Ahmed F. Elaksher1; Abdullatif A. Alharthy2
1Faculty of Engineering, Cairo University
2Faculty of Engineering, Umm Al-Qura University
Abstract
Satellite images are the main source for different change detection applications. These images are usually taken from different sensors at different times. Hence, the point correspondence is not established. In this paper, the Singular Value Decomposition (SVD) is used to automatically solve the point correspondence problem between satellite images with different attributes. For each pair of the images, a cost matrix is built. The cost of corresponding any two points in a pair of images is computed using different geometric attributes. The SVD for the cost matrix is then used to solve the point correspondence problem. The algorithm is tested on QuickBird, IKONOS, and SPOT images. Results showed that using the traditional Euclidean distance cost matrix is not suitable for remote sensing images. Hence, a modified cost matrix was introduced based on the orientation parameters of the satellite images. The new cost matrix is then computed and its SVD is calculated. Results showed significant improvement in the solution of the point corresponding problem regardless the size or orientation of the satellite images.
Keywords
Point Correspondence; Satellite Images; Transformation Models- SVD; Matching
Main Subjects
Civil Engineering: structural, Geotechnical, reinforced concrete and steel structures, Surveying, Road and traffic engineering, water resources, Irrigation structures, Environmental and sanitary engineering, Hydraulic, Railway, construction Management.
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