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Multimodal remote sensing image registration using multiscale self-similarities

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4 Author(s)
Hao Sun ; School of Electronic Science and Engineering, National University of Defense Technology, Changsha, China ; Lin Lei ; Huanxin Zou ; Cheng Wang

Motivated by the recent success of self-similarity in computer vision research, this paper proposed an approach for multimodal remote sensing image registration exploiting multiscale self-similarities (MSS) descriptor and coherent point sets analysis based on Gaussian mixture model (GMM) fitting. Rather than extracting sparse features for matching, we compute MSS descriptor at a regular grid. Point sets are selected according to their MSS descriptor similarity. Experimental results demonstrate the efficiency and the accuracy of the proposed technique for multimodal remote sensing image registration.

Published in:

Computer Vision in Remote Sensing (CVRS), 2012 International Conference on

Date of Conference:

16-18 Dec. 2012