Research Papers

Simulation of remote sensing imaging motion blur based on image motion vector field

[+] Author Affiliations
Huijie Zhao

Beihang University, School of Instrument Science and Opto-Electronics Engineering, Ministry of Education, Key Laboratory of Precision Opto-Mechatronics Technology, Xueyuan Road 37, Haidian District, Beijing 100191, China

Hong Shang

Beihang University, School of Instrument Science and Opto-Electronics Engineering, Ministry of Education, Key Laboratory of Precision Opto-Mechatronics Technology, Xueyuan Road 37, Haidian District, Beijing 100191, China

Guorui Jia

Beihang University, School of Instrument Science and Opto-Electronics Engineering, Ministry of Education, Key Laboratory of Precision Opto-Mechatronics Technology, Xueyuan Road 37, Haidian District, Beijing 100191, China

J. Appl. Remote Sens. 8(1), 083539 (Oct 29, 2014). doi:10.1117/1.JRS.8.083539
History: Received May 30, 2014; Revised September 2, 2014; Accepted September 3, 2014
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Abstract.  The motion blur simulation technique is widely used in remote sensing of an image chain simulation. However, the traditional method, which models the motion blur through a point spread function (PSF), is not precise enough when the imaging area is rugged or the motion of the platform is unstable. A physically based simulation model of motion blur is proposed. The model uses an image motion vector (IMV) field to describe the relative motion presented on the image plane during the exposure time. Based on the IMV field, the opto-electrons blurring model is built to simulate the blurring effect. A physical experiment was made to validate the model. The experiment result demonstrates that the simulation result generated by the model provided is more precise than the traditional PSF method, and a more complex motion status can be presented by the proposed method.

© 2014 Society of Photo-Optical Instrumentation Engineers

Citation

Huijie Zhao ; Hong Shang and Guorui Jia
"Simulation of remote sensing imaging motion blur based on image motion vector field", J. Appl. Remote Sens. 8(1), 083539 (Oct 29, 2014). ; http://dx.doi.org/10.1117/1.JRS.8.083539


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