
Proceedings Paper
An integral design strategy combining optical system and image processing to obtain high resolution imagesFormat | Member Price | Non-Member Price |
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Paper Abstract
In this paper, an integral design that combines optical system with image processing is introduced to obtain high resolution images, and the performance is evaluated and demonstrated. Traditional imaging methods often separate the two technical procedures of optical system design and imaging processing, resulting in the failures in efficient cooperation between the optical and digital elements. Therefore, an innovative approach is presented to combine the merit function during optical design together with the constraint conditions of image processing algorithms. Specifically, an optical imaging system with low resolution is designed to collect the image signals which are indispensable for imaging processing, while the ultimate goal is to obtain high resolution images from the final system. In order to optimize the global performance, the optimization function of ZEMAX software is utilized and the number of optimization cycles is controlled. Then Wiener filter algorithm is adopted to process the image simulation and mean squared error (MSE) is taken as evaluation criterion. The results show that, although the optical figures of merit for the optical imaging systems is not the best, it can provide image signals that are more suitable for image processing. In conclusion. The integral design of optical system and image processing can search out the overall optimal solution which is missed by the traditional design methods. Especially, when designing some complex optical system, this integral design strategy has obvious advantages to simplify structure and reduce cost, as well as to gain high resolution images simultaneously, which has a promising perspective of industrial application.
Paper Details
Date Published: 19 May 2016
PDF: 7 pages
Proc. SPIE 9874, Remotely Sensed Data Compression, Communications, and Processing XII, 98740F (19 May 2016); doi: 10.1117/12.2224394
Published in SPIE Proceedings Vol. 9874:
Remotely Sensed Data Compression, Communications, and Processing XII
Bormin Huang; Chein-I Chang; Chulhee Lee, Editor(s)
PDF: 7 pages
Proc. SPIE 9874, Remotely Sensed Data Compression, Communications, and Processing XII, 98740F (19 May 2016); doi: 10.1117/12.2224394
Show Author Affiliations
Jiaoyang Wang, Xidian Univ. (China)
No. 203 Research Institute of China, Ordnance Industries (China)
Lin Wang, Xidian Univ. (China)
Ying Yang, Xidian Univ. (China)
Rui Gong, Xidian Univ. (China)
No. 203 Research Institute of China, Ordnance Industries (China)
Lin Wang, Xidian Univ. (China)
Ying Yang, Xidian Univ. (China)
Rui Gong, Xidian Univ. (China)
Xiaopeng Shao, Xidian Univ. (China)
Chao Liang, No. 203 Research Institute of China, Ordnance Industries (China)
Jun Xu, Xidian Univ. (China)
Chao Liang, No. 203 Research Institute of China, Ordnance Industries (China)
Jun Xu, Xidian Univ. (China)
Published in SPIE Proceedings Vol. 9874:
Remotely Sensed Data Compression, Communications, and Processing XII
Bormin Huang; Chein-I Chang; Chulhee Lee, Editor(s)
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