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	Conservation and restoration efforts have promoted increases in shorebird populations and the area and quality of their habitat in the Yellow River Delta, China 期刊论文 OAI收割 INTERNATIONAL JOURNAL OF DIGITAL EARTH, 2023, 卷号: 16, 期号: 2, 页码: 4126-4140 作者: Duan, Houlang; Xia, Shaoxia; Yu, Xiubo \| 收藏 \| 浏览/下载：16/0 \| 提交时间：2023/11/06 Shorebirds habitat degradation loss of shorebird diversity conservation and restoration Yellow River Delta
	Adaptive Wiener filtering with Gaussian fitted point spread function in image restoration (EI CONFERENCE) 会议论文 OAI收割 2011 IEEE 2nd International Conference on Software Engineering and Service Science, ICSESS 2011, July 15, 2011 - July 17, 2011, Beijing, China 作者: Yang L.; Zhang X.; Zhang X.; Zhang X.; Yang L. 收藏 \| 浏览/下载：44/0 \| 提交时间：2013/03/25 In the imaging process of the space remote sensing camera there was degradation phenomenon in the acquired images. In order to reduce the image blur caused by the degradation the remote sensing images were restored to give prominence to the characteristic objects in the images. First the frequency-domain notch filter was adopted to remove strip noises in the images. Then using the ground characters with the knife-edge shape in the images the point spread function of the imaging system was estimated. In order to improve the accuracy the estimated point spread function was corrected with Gaussian fitting method. Finally the images were restored using the adaptive Wiener filtering with the fitted point spread function. Experimental results of the real remote sensing images showed that almost all strip noises in the images were eliminated. After the denoised images were restored its variance and its gray mean gradient increased also its laplacian gradient increased. Restoration with Gaussian fitted point spread function is beneficial to interpreting and analyzing the remote sensing images. After restoration the blur phenomenon of the images is reduced. The characters are highlighted and the visual effect of the images is clearer. 2011 IEEE.
	Remote sensing image restoration using estimated point spread function (EI CONFERENCE) 会议论文 OAI收割 2010 International Conference on Information, Networking and Automation, ICINA 2010, October 17, 2010 - October 19, 2010, Kunming, China 作者: Yang L.; Yang L. 收藏 \| 浏览/下载：32/0 \| 提交时间：2013/03/25 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.
	Restoration of an atmospherically blurred image based on physical model fusion approach (EI CONFERENCE) 会议论文 OAI收割 2010 IEEE 10th International Conference on Signal Processing, ICSP2010, October 24, 2010 - October 28, 2010, Beijing, China 作者: Wang Y.; Li J.; Li J.; Li J.; Wang Y. 收藏 \| 浏览/下载：26/0 \| 提交时间：2013/03/25 This paper proposes a new restoration method only using the single image information combining atmospheric physical model with fusion techniques to reduce the degradation of the image contrast in bad weather conditions caused by atmospheric aerosols such as haze and fog. The basic idea of this method is to utilize physics-based model method instead of multisensors to generate a serial of virtual images and then to fuse those virtual images into a high contrast image based on the wavelet fusion technique. In contrast to previous methods our restoration technique is not only independent on predicted structure distributions of scene reflectance or detailed knowledge about the particular weather condition but also adapt to the situation without a reference image or images with moving objects captured by a video camera. Experiments on different poorcontrast images demonstrate the availability of the proposed method in case of restoring the atmospherically blurred images. 2010 IEEE.
	Degradation and restoration of forest ecosystems in China SCI/SSCI论文 OAI收割 2004 Li W. H. 收藏 \| 浏览/下载：25/0 \| 提交时间：2012/06/08 sustainable forestry forest resources ecosystem management shelterbelts nature reserves degradation and restoration of ecosystems reforestation afforestation agroforestry