Remote Sensing Image Restoration Based on an improved Landweber Iterative Method for Forest Monitoring and Management
Xizhi Lv, Zhongguo Zuo, Zhihui Wang, Li Li, Jing Huang · IOP Conference Series Earth and Environmental Science · 2018
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.