Self Tuning Kalman Filter Estimation of Atmospheric Warp

被引：6

作者：

Tahtali, Murat ^{[1
]}

Lambert, Andrew ^{[2
]}

Fraser, Donald ^{[2
]}

机构：

[1] UNSW ADFA, Sch Aerosp Civil & Mech Engn, Canberra, ACT 2600, Australia

[2] UNSW ADFA, Sch Informat Technol & Elect Engn, Canberra, ACT 2600, Australia

来源：

IMAGE RECONSTRUCTION FROM INCOMPLETE DATA V | 2008年 / 7076卷

关键词：

Kalman filter; image registration; shiftmaps; atmospheric warp; image restoration;

D O I：

10.1117/12.795888

中图分类号：

TH7 [仪器、仪表];

学科分类号：

0804 ; 080401 ; 081102 ;

摘要：

In our previous work we have demonstrated that the perceived wander of image intensities as seen through the windows" of each pixel due to atmospheric turbulence can be modelled as a simple oscillator pixel-by-pixel and a linear Kalman filter (KF) can be finetuned to predict to a certain extent short term future deformations. In this paper, we are expanding the Kalman filter into a Hybrid Extended Kalman filter (HEKF) to fine tune itself by relaxing the oscillator parameters at each individual pixel. Results show that HEKF performs significantly better than linear KF.

引用

页数：12