Remote Sensing Image Restoration Based on an improved Landweber Iterative Method for Forest Monitoring and Management

2018 2nd International Workshop on Renewable Energy and Development

能源学;经济学

Lv, Xizhi^1 ; Zuo, Zhongguo^1 ; Wang, Zhihui^1 ; Li, Li^1 ; Huang, Jing^1

Yellow River Institute of Hydraulic Research, Key Lab. of the Loess Plateau Soil Erosion and Water Loss Proc. and Contr. of Min. of Water Rsrc., Zhengzhou, HENAN

450003, China^1

关键词: Environmental constraints;    Forest monitoring;    Landweber iteration methods;    Remote sensing images;    Remote sensing imaging;    Remote sensing technology;    Restoration methods;    Space Exploration Technologies;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/153/6/062085/pdf
DOI  :  10.1088/1755-1315/153/6/062085

来源: IOP

【 摘 要 】

As an advanced space exploration technologies, remote sensing technology has been widely used in forest monitoring and management. Forest current conditions could be reflected in real-time remote sensing images, but due to various imaging system and its environmental constraints, the original remote sensing images is often blurred. In this paper, two common remote-sensing imaging blurs, named motion blur and atmospheric turbulence blur, were studied and discussed the mechanism of the image blurred, and proposed a remote sensing image restoration method based on an improved Landweber iteration method which expedites the convergence only in the signal domain. As a result, we can still improve the image restoration accuracy of results at the same time of speeding up convergences.