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Remote sensing image restoration using estimated point spread function (EI CONFERENCE) 会议论文
2010 International Conference on Information, Networking and Automation, ICINA 2010, October 17, 2010 - October 19, 2010, Kunming, China
Yang L.; Ren J.
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In order to reduce image blur caused by the degradation phenomenon in the imaging process  the acquired images of the space remote sensing camera are restored. First  the frequency-domain notch filter is adopted to remove strip noises in the images. Then degradation function  which is referred to as the point spread function (PSF) of the imaging system is estimated using the knife-edge method. To improve the accuracy of the estimation  the estimated PSF is adjusted with Gaussian fitting. Finally  the images are restored by Wiener filtering with the fitted PSF. The restoration results of the remote sensing images show that almost all strip noises are eliminated by the notch filter. After denoising and restoration  the variance of the remote sensing image worked with in this paper increases 30.979 and the gray mean gradient increases 3.312. Due to Gaussian fitting  the accuracy of the PSF estimation is heightened. Image restoration with the final PSF is benefit to interpreting and analyzing the remote sensing images. After restoration  the contrasts of the restored images are increased and the visual effects become clearer. 2010 IEEE.  


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