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Proceedings Paper

Error analysis and performance estimation of two different mathematical methods for image registration
Author(s): Prakash Duraisamy; Yao Shen; Kamesh Namuduri; Steve Jackson
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Paper Abstract

This paper discusses the error analysis and performance estimation between two different mathematical methods for registering a sequence of images taken by an airborne sensor. Here both methods use homography matrices to obtain the panoramic image, but they use different mathematical techniques to obtain the same result. In Method-I, we use Discrete Linear Transform and Singular Value Decomposition to obtain the homographies and in Method-II we use the Levenberg-Marquardt algorithm as iterative technique to re-estimate the homography in order to obtain the same panoramic image. These two methods are analyzed, compared based on reliability and robustness of registration. We also compare their performance using an error metric that compares their registration accuracies with respect to ground truth. Our results demonstrate that Levenberg-Marquardt algorithm clearly outperforms Discrete Linear Transform algorithm.

Paper Details

Date Published: 15 September 2010
PDF: 9 pages
Proc. SPIE 7799, Mathematics of Data/Image Coding, Compression, and Encryption with Applications XII, 77990O (15 September 2010); doi: 10.1117/12.861104
Show Author Affiliations
Prakash Duraisamy, Univ. of North Texas (United States)
Yao Shen, Univ. of North Texas (United States)
Kamesh Namuduri, Univ. of North Texas (United States)
Steve Jackson, Univ. of North Texas (United States)


Published in SPIE Proceedings Vol. 7799:
Mathematics of Data/Image Coding, Compression, and Encryption with Applications XII
Mark S. Schmalz; Gerhard X. Ritter; Junior Barrera; Jaakko T. Astola, Editor(s)

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