EDA Based Motion Deblurring for Sandroid CubeSats Imaging System

IF 0.7 4区 计算机科学 Q4 AUTOMATION & CONTROL SYSTEMS
Xiaoqiang Wu, Fengge Wu, Junsuo Zhao, Zhenghui Liu
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引用次数: 0

Abstract

Motion blur, which increases the difficulty of locating and identifying target objects, has always been an ill-posed issue of space-based imaging system. In our paper, we point out the issue of deblurring degraded images caused by relative motion between space-based imaging system and observation targets. Such as motion of target objects to be observed or tremors of space-based imaging system. We propose a strategy to deblur degraded images that uses Estimation of Distribution Algorithm to obtain a better motion blur kernel in both linear and non-linear non-blind deconvolution situations. To produce a deblurred result, the strategy will be applied on a single image collected from the space-based imaging system on our Sandroid CubeSats, a member of NanoSats. Sandroid bases on Android operating system and our Sandroid CubeSats make full use of mobile device cluster as the main support of computing resources. Currently, the superior on-board computing capability of our Sandroid CubeSats makes sure that the proposed strategy is operative. In addition, experimental results prove that the proposed strategy is efficient and effective.
基于EDA的sandoid立方体卫星成像系统运动去模糊
运动模糊增加了目标物体的定位和识别难度,一直是天基成像系统的不适定问题。本文提出了天基成像系统与观测目标之间的相对运动所引起的退化图像的去模糊问题。如观察目标物体的运动或天基成像系统的震动。在线性和非线性非盲反卷积情况下,我们提出了一种使用分布估计算法来获得更好的运动模糊核的退化图像去模糊策略。为了产生去模糊的结果,该策略将应用于从我们的NanoSats成员Sandroid CubeSats的天基成像系统收集的单个图像。Sandroid基于Android操作系统,我们的Sandroid立方体卫星充分利用移动设备集群作为计算资源的主要支撑。目前,我们的Sandroid立方体卫星优越的机载计算能力确保了所提出的策略是可行的。实验结果证明了该策略的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Modeling Identification and Control
Modeling Identification and Control 工程技术-计算机:控制论
CiteScore
3.30
自引率
0.00%
发文量
6
审稿时长
>12 weeks
期刊介绍: The aim of MIC is to present Nordic research activities in the field of modeling, identification and control to the international scientific community. Historically, the articles published in MIC presented the results of research carried out in Norway, or sponsored primarily by a Norwegian institution. Since 2009 the journal also accepts papers from the other Nordic countries.
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