22 September 2016 Motion deblurring based on local temporal compressive sensing for remote sensing image
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Abstract
This paper presents a motion deblurring method which can obtain both the motion information and the recovered image based on local temporal compressive photography. In this method, video blocks are reconstructed at the corners of the image sensor during a single exposure period. The displacement vector, which will be used to build the prior point spread function (PSF) for image deblurring, is then estimated from the reconstructed videos. With the use of the prior PSF, better recovered images can be obtained with much less iteration. An experiment system is also presented to validate the effectiveness of the proposed method. The experimental results show that the proposed method could provide recovered images of high quality.
© 2016 Society of Photo-Optical Instrumentation Engineers (SPIE)
Chaoying Tang, Yueting Chen, Huajun Feng, Zhihai Xu, Qi Li, "Motion deblurring based on local temporal compressive sensing for remote sensing image," Optical Engineering 55(9), 093106 (22 September 2016). https://doi.org/10.1117/1.OE.55.9.093106 . Submission:
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