Application of a dynamic feature selection algorithm to multi-sensor image registration

Stephen DelMarco; Victor Tom; Helen Webb; David Lefebvre

doi:10.1117/12.713922

7 May 2007 Application of a dynamic feature selection algorithm to multi-sensor image registration

Stephen DelMarco, Victor Tom, Helen Webb, David Lefebvre

Proceedings Volume 6567, Signal Processing, Sensor Fusion, and Target Recognition XVI; 656717 (2007) https://doi.org/10.1117/12.713922
Event: Defense and Security Symposium, 2007, Orlando, Florida, United States

Abstract

Image registration is usually a required first processing step for such activities as surveillance, video tracking, change detection, and remote sensing. Often, different sensors are used for the collection of the test and reference imagery. The sensor phenomenology differences can present problems for automatic selection of registration algorithm parameters because of different cross-sensor feature manifestation. In previous work involving edge-based multisensor image registration, we applied a previously-developed automated approach to parameter selection, designed specifically for edge detection. In this work, we adapt and apply a dynamic feature selection algorithm (DFSA) that we recently developed for use in registration algorithm selection for registering images with varying scene content type. We adapt and apply the DFSA to the problem of selecting appropriate registration algorithm parameter values in an edge-based registration algorithm. The approach involves generating test-to-reference feature match scores over a sampling of the transform hypothesis space. The approach is scene-adaptive thereby requiring no a priori information on image scene content. Furthermore, in the DFSA we leverage prior match score calculation generated in a hierarchical grid search to reduce additional computational expense. We give a brief overview of the registration algorithmic framework, and present a description of the dynamic feature selection algorithm. Numerical results are presented for performing test SAR-to-reference EO image registration to show the registration convergence performance improvement resulting from use of the DFSA. Numerical results are generated over images exhibiting different scene content types. We also evaluate the effect of match score normalization on the registration convergence performance improvement.

Citation Download Citation

Stephen DelMarco, Victor Tom, Helen Webb, and David Lefebvre "Application of a dynamic feature selection algorithm to multi-sensor image registration", Proc. SPIE 6567, Signal Processing, Sensor Fusion, and Target Recognition XVI, 656717 (7 May 2007); https://doi.org/10.1117/12.713922

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