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Proceedings Paper

Real-world multisensor image alignment using edge focusing and Hausdorff distances
Author(s): Yunlong Sheng; Xiangjie Yang; Daniel McReynolds; Zhong Zhang; Langis Gagnon; Leandre Sevigny
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Paper Abstract

The area-based methods, such as using Laplacian pyramid and Fourier transform-based phase matching, benefit by highlighting high spatial frequencies to reduce sensitivity to the feature inconsistency problem in the multisensor image registration. The feature extraction and matching methods are more powerful and versatile to process poor quality IR images. We implement multi-scale hierarchical edge detection and edge focusing and introduce a new salience measure for the horizon, for multisensor image registration. The common features extracted from images of two modalities can be still different in detail. Therefore, the transformation space match methods with the Hausdorff distance measure is more suitable than the direct feature matching methods. We have introduced image quadtree partition technique to the Hausdorff distance matching, that dramatically reduces the size of the search space. Image registration of real world visible/IR images of battle fields is shown.

Paper Details

Date Published: 12 March 1999
PDF: 12 pages
Proc. SPIE 3719, Sensor Fusion: Architectures, Algorithms, and Applications III, (12 March 1999); doi: 10.1117/12.341340
Show Author Affiliations
Yunlong Sheng, Univ. Laval (Canada)
Xiangjie Yang, Univ. Laval (Canada)
Daniel McReynolds, Univ. Laval (Canada)
Zhong Zhang, Univ. Laval (Canada)
Langis Gagnon, Lockheed Martin Canada (Canada)
Leandre Sevigny, Defence Research Establishment Valcartier (Canada)


Published in SPIE Proceedings Vol. 3719:
Sensor Fusion: Architectures, Algorithms, and Applications III
Belur V. Dasarathy, Editor(s)

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