A Restoration Method of Blurred Remote Sensing Images Based on Total Variation Optimization
Yiyun Man · Keji daobao · 2011
In view of blurred remote sensing images with the noise resulted in some degradations during imaging and transmission processes,a kind of restoration method is proposed based on MTF estimation and total variation optimization.The restoration principle of blurred remote sensing images with noise is elucidated in depth through a thorough analysis of frequency characteristics of MTF.In order to deal with the noise,a new piecewise approximation strategy for MTF estimation is employed,which has the general applicability and outperforms the conventional models in overcoming noise disturbance by experiment demonstrations.Moreover,aiming at the restoration processing of blurred remote sensing images with noise,an improved method of fast total variation optimization is adopted to achieve the optimal restoration effect.A series of experimental results indicate that proposed restoration method could preserve more details and texture information of images besides its satisfactory performance of eliminating noise,thus it could provide an effective approach to the restoration processing of remote sensing images with heavy noise.