
Proceedings Paper
A framework for small infrared target real-time visual enhancementFormat | Member Price | Non-Member Price |
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Paper Abstract
This paper proposes a framework for small infrared target real-time visual enhancement. The framework is consisted of three parts: energy accumulation for small infrared target enhancement, noise suppression and weighted fusion. Dynamic programming based track-before-detection algorithm is adopted in the energy accumulation to detect the target accurately and enhance the target’s intensity notably. In the noise suppression, the target region is weighted by a Gaussian mask according to the target’s Gaussian shape. In order to fuse the processed target region and unprocessed background smoothly, the intensity in the target region is treated as weight in the fusion. Experiments on real small infrared target images indicate that the framework proposed in this paper can enhances the small infrared target markedly and improves the image’s visual quality notably. The proposed framework outperforms tradition algorithms in enhancing the small infrared target, especially for image in which the target is hardly visible.
Paper Details
Date Published: 18 March 2015
PDF: 6 pages
Proc. SPIE 9443, Sixth International Conference on Graphic and Image Processing (ICGIP 2014), 94430N (18 March 2015); doi: 10.1117/12.2178807
Published in SPIE Proceedings Vol. 9443:
Sixth International Conference on Graphic and Image Processing (ICGIP 2014)
Yulin Wang; Xudong Jiang; David Zhang, Editor(s)
PDF: 6 pages
Proc. SPIE 9443, Sixth International Conference on Graphic and Image Processing (ICGIP 2014), 94430N (18 March 2015); doi: 10.1117/12.2178807
Show Author Affiliations
Xiaoliang Sun, National Univ. of Defense Technology (China)
Hunan Provincial Key Lab. of Image Measurement and Vision Navigation (China)
Gucan Long, National Univ. of Defense Technology (China)
Hunan Provincial Key Lab. of Image Measurement and Vision Navigation (China)
Hunan Provincial Key Lab. of Image Measurement and Vision Navigation (China)
Gucan Long, National Univ. of Defense Technology (China)
Hunan Provincial Key Lab. of Image Measurement and Vision Navigation (China)
Yang Shang, National Univ. of Defense Technology (China)
Hunan Provinical Key Lab. of Image Measurement and Vision Navigation (China)
Xiaolin Liu, National Univ. of Defense Technology (China)
Hunan Provinical Key Lab. of Image Measurement and Vision Navigation (China)
Xiaolin Liu, National Univ. of Defense Technology (China)
Published in SPIE Proceedings Vol. 9443:
Sixth International Conference on Graphic and Image Processing (ICGIP 2014)
Yulin Wang; Xudong Jiang; David Zhang, Editor(s)
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