Impact of infrared sensor scanning control accuracy on super-resolution reconstruction

Xiaochong Tong; Zhiyuan Qin; Bing Wu; He Li; Guangling Lai; Lu Ding

doi:10.1117/1.JRS.11.016031

23 February 2017 Impact of infrared sensor scanning control accuracy on super-resolution reconstruction

Xiaochong Tong, Zhiyuan Qin, Bing Wu, He Li, Guangling Lai, Lu Ding

Author Affiliations +

Journal of Applied Remote Sensing, Vol. 11, Issue 1, 016031 (February 2017). https://doi.org/10.1117/1.JRS.11.016031

Abstract

An important area of research for super-resolution reconstruction is the issue of motion estimation or mutual registration. Currently, the majority of domestic and international research focuses on registration or estimation methods. However, the reverse approach has not been considered, i.e., investigating the impact of the accuracy of motion estimation or registration on the quality of the reconstructed images, the relationship between the above-mentioned impact and the accuracy of motion estimation, and whether this relationship is quantifiable. There remains a lack of theoretical and systematic studies on these issues. By discussing super-resolution reconstruction of infrared scanning images while focusing on the impact of the registration error caused by the control system of the scanning device, the above mentioned issues are addressed. Nonlinear error transfer methods and impact analysis of blur parameters were conducted using both low-frequency and high-frequency information. After obtaining the theoretical results, experiments were performed to verify the accuracy of those results. The findings of this study can be used not only as guidelines for the theoretical evaluation of super-resolution reconstructed images but also to determine the design parameters of sensors and provide theoretical support for the design indicators of sensor control systems.

Citation Download Citation

Xiaochong Tong, Zhiyuan Qin, Bing Wu, He Li, Guangling Lai, and Lu Ding "Impact of infrared sensor scanning control accuracy on super-resolution reconstruction," Journal of Applied Remote Sensing 11(1), 016031 (23 February 2017). https://doi.org/10.1117/1.JRS.11.016031

Received: 7 October 2016; Accepted: 2 February 2017; Published: 23 February 2017

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