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Joint image restoration and location in visual navigation system
Author(s): Yuefeng Wu; Nong Sang; Wei Lin; Yuanjie Shao
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Paper Abstract

Image location methods are the key technologies of visual navigation, most previous image location methods simply assume the ideal inputs without taking into account the real-world degradations (e.g. low resolution and blur). In view of such degradations, the conventional image location methods first perform image restoration and then match the restored image on the reference image. However, the defective output of the image restoration can affect the result of localization, by dealing with the restoration and location separately. In this paper, we present a joint image restoration and location (JRL) method, which utilizes the sparse representation prior to handle the challenging problem of low-quality image location. The sparse representation prior states that the degraded input image, if correctly restored, will have a good sparse representation in terms of the dictionary constructed from the reference image. By iteratively solving the image restoration in pursuit of the sparest representation, our method can achieve simultaneous restoration and location. Based on such a sparse representation prior, we demonstrate that the image restoration task and the location task can benefit greatly from each other. Extensive experiments on real scene images with Gaussian blur are carried out and our joint model outperforms the conventional methods of treating the two tasks independently.

Paper Details

Date Published: 19 February 2018
PDF: 6 pages
Proc. SPIE 10608, MIPPR 2017: Automatic Target Recognition and Navigation, 106080A (19 February 2018); doi: 10.1117/12.2284978
Show Author Affiliations
Yuefeng Wu, Huazhong Univ. of Science and Technology (China)
Nong Sang, Huazhong Univ. of Science and Technology (China)
Wei Lin, Huazhong Univ. of Science and Technology (China)
Yuanjie Shao, Huazhong Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 10608:
MIPPR 2017: Automatic Target Recognition and Navigation
Jianguo Liu; Jayaram K. Udupa; Hanyu Hong, Editor(s)

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