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Proceedings Paper

The infrared image closely spaced objects super resolution method based on sparse reconstruction under the noise environment
Author(s): Jian Zeng; Jungang Yang; Hanyang Wu
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Paper Abstract

Super-resolution method based on sparse reconstruction is an effective way to deal with the closely spaced objects problem, but when the targets in a noisy environment, the noise will cover over the entire field, leading to the sparsity feature of the original scene is destroyed. Aiming at this phenomenon, this paper proposed a super-resolution method which has the adaptative reconstruction ability in noisy environments, this method takes full advantage of the structural characteristics of the sensor and the reconstruction algorithm parameters, through the establishment of infrared imaging model of the observed signals and pixel meshing, establishment of the position and amplitude of the closely spaced objects of sparse representation, and using the point spread function of the optical system to construct over-complete dictionary, the last step is making the reconstruction parameters in a reasonable range through controlling the ratio of non-zero elements in the rebuilt scene, so as to achieve the purpose of removing noise interference and reconstruction of sparse targets accurately. Simulation results show that the proposed method with adaptive reconfiguration in noisy environments.

Paper Details

Date Published: 10 February 2017
PDF: 7 pages
Proc. SPIE 10250, International Conference on Optical and Photonics Engineering (icOPEN 2016), 102502V (10 February 2017); doi: 10.1117/12.2266856
Show Author Affiliations
Jian Zeng, National Univ. of Defense Technology (China)
Jungang Yang, National Univ. of Defense Technology (China)
Hanyang Wu, National Univ. of Defense Technology (China)

Published in SPIE Proceedings Vol. 10250:
International Conference on Optical and Photonics Engineering (icOPEN 2016)
Anand Krishna Asundi; Xiyan Huang; Yi Xie, Editor(s)

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