Turbulence stabilization

被引：0
|
作者：
Mao, Yu [1 ]
Gilles, Jerome [1 ]
机构：
[1] Univ Minnesota, Inst Math & Its Applicat, Minneapolis, MN 55455 USA
来源：
INFRARED IMAGING SYSTEMS: DESIGN, ANALYSIS, MODELING, AND TESTING XXIII | 2012年 / 8355卷
关键词：
Stabilization; Turbulence restoration; Regularization constraints; Bregman Iterations; BLIND; REGULARIZATION; ALGORITHMS; DECONVOLUTION; CONVERGENCE; SUM;
D O I：
10.1117/12.917964
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
We recently developed a new approach to get a stabilized image from a sequence of frames acquired through atmospheric turbulence. The goal of this algorihtm is to remove the geometric distortions due by the atmosphere movements. This method is based on a variational formulation and is efficiently solved by the use of Bregman iterations and the operator splitting method. In this paper we propose to study the influence of the choice of the regularizing term in the model. Then we proposed to experiment some of the most used regularization constraints available in the litterature.
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页数：7
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