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Practical image registration concerns overcome by the weighted and filtered mutual information metric

[+] Author Affiliations
Tommy P. Keane

Rochester Institute of Technology, Chester F. Carlson Center for Imaging Science, 54 Lomb Memorial Drive, Rochester, New York 14623

Eli Saber

Rochester Institute of Technology, Department of Electrical and Microelectronic Engineering, 54 Lomb Memorial Drive, Rochester, New York 14623

Harvey Rhody

Rochester Institute of Technology, Chester F. Carlson Center for Imaging Science, 54 Lomb Memorial Drive, Rochester, New York 14623

Andreas Savakis

Rochester Institute of Technology, Department of Computer Engineering, 54 Lomb Memorial Drive, Rochester, New York 14623

Jeffrey Raj

Lenel Systems International Inc., A UTC Fire & Security Company, 1212 Pittsford-Victor Road, Pittsford, New York 14534

J. Electron. Imaging. 21(2), 023029 (Jun 27, 2012). doi:10.1117/1.JEI.21.2.023029
History: Received August 17, 2011; Revised February 13, 2012; Accepted March 30, 2012
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Abstract.  Contemporary research in automated panorama creation utilizes camera calibration or extensive knowledge of camera locations and relations to each other to achieve successful results. Research in image registration attempts to restrict these same camera parameters or apply complex point-matching schemes to overcome the complications found in real-world scenarios. This paper presents a novel automated panorama creation algorithm by developing an affine transformation search based on maximized mutual information (MMI) for region-based registration. Standard MMI techniques have been limited to applications with airborne/satellite imagery or medical images. We show that a novel MMI algorithm can approximate an accurate registration between views of realistic scenes of varying depth distortion. The proposed algorithm has been developed using stationary, color, surveillance video data for a scenario with no a priori camera-to-camera parameters. This algorithm is robust for strict- and nearly-affine-related scenes, while providing a useful approximation for the overlap regions in scenes related by a projective homography or a more complex transformation, allowing for a set of efficient and accurate initial conditions for pixel-based registration.

© 2012 SPIE and IS&T

Citation

Tommy P. Keane ; Eli Saber ; Harvey Rhody ; Andreas Savakis and Jeffrey Raj
"Practical image registration concerns overcome by the weighted and filtered mutual information metric", J. Electron. Imaging. 21(2), 023029 (Jun 27, 2012). ; http://dx.doi.org/10.1117/1.JEI.21.2.023029


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