Paper
24 October 2007 A new target association algorithm based on invariant features in remote sensing images
Author Affiliations +
Abstract
There are two problems when associating multiple targets in remote sensing images: Firstly, with low temporal resolution observation, the target's kinematic state cannot be estimated accurately and the classical Kalman filtering association algorithms are no more applicable. Secondly, the classical image feature-based target matching algorithms cannot deal with the illegibility of multiple targets' correspondence, which don't take into account the uncertainty of feature extraction. To resolve above problems, a novel multiple targets association method based on Multi-scale Autoconvolution(MSA) features matching and global association cost optimization through simulated annealing (SA) algorithm is proposed. Experiments with remote sensing images show the applicability of the method for multiple targets association.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Lin Lei, Yi Su, and Zhiyong Li "A new target association algorithm based on invariant features in remote sensing images", Proc. SPIE 6748, Image and Signal Processing for Remote Sensing XIII, 67481B (24 October 2007); https://doi.org/10.1117/12.737626
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Cited by 1 scholarly publication.
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KEYWORDS
Detection and tracking algorithms

Remote sensing

Image fusion

Optimization (mathematics)

Algorithms

Chemical species

Metals

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