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Proceedings Paper

Fast image registration via joint gradient maximization: application to multi-modal data
Author(s): Xue Mei; Fatih Porikli
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Paper Abstract

We present a computationally inexpensive method for multi-modal image registration. Our approach employs a joint gradient similarity function that is applied only to a set high spatial gradient pixels. We obtain motion parameters by maximizing the similarity function by gradient ascent method, which secures a fast convergence. We apply our technique to the task of affine model based registration of 2D images which undergo large rigid motion, and show promising results.

Paper Details

Date Published: 5 October 2006
PDF: 5 pages
Proc. SPIE 6395, Electro-Optical and Infrared Systems: Technology and Applications III, 63950P (5 October 2006); doi: 10.1117/12.690077
Show Author Affiliations
Xue Mei, Univ. of Maryland (United States)
Fatih Porikli, Mitsubishi Electric Research Labs (United States)

Published in SPIE Proceedings Vol. 6395:
Electro-Optical and Infrared Systems: Technology and Applications III
Ronald G. Driggers; David A. Huckridge, Editor(s)

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