星空观测图像目标拖尾的自动消除

张健; 任建存; 张春华

星空观测图像目标拖尾的自动消除

1.
海军航空工程学院控制工程系,山东烟台 264001;
2.
中国人民解放军61741部队信息中心,北京 100094

详细信息

通讯作者:
张健（1979-），男，河南汝州人，博士研究生，工程师，主要从事图像弱小目标检测方面的研究工作。 Email: zhangjian101824@sohu.com

中图分类号: TN911.73; TN247
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出版历程
- 刊出日期: 2013-01-15

Automatic de-smearing algorithm for target in space observation image

1.
Department of Control Engineering,Naval Aeronautical and Astronautical University,Yantai 264001,China;
2.
Information Center, Unit 61741 of PLA,Beijing 100094,China

摘要

摘要: 为了实现对星空观测图像中高亮目标产生的拖尾现象进行自动消除，建立了目标拖尾自动消除系统，对该系统所采用的图像背景高斯噪声分布参数估计、目标拖尾检测以及图像灰度值校正等算法进行研究。利用直方图最小二乘曲线拟合估计星空观测图像背景高斯噪声的分布参数；利用观测图像中目标拖尾现象的特征提出一种基于统计信息的拖尾检测算法；在确定目标拖尾位置的基础上对被污染的像素进行灰度值校正；利用Visual Studio 2005开发出一套星空观测图像目标拖尾自动消除系统。实验结果表明：针对16 bit，1 0241 024的星空观测图像，单帧图像处理时间约为300 ms，拖尾现象得到消除，恒星和目标等有用信息未被破坏。本文算法基本满足后续观测图像中弱小目标检测稳定、可靠、精度高等要求。
- 信号与信息处理 /
- 拖尾现象 /
- 最小二乘曲线拟合 /
- 灰度值校正 /
- 梯度变量
Abstract: In order to realize automatic correction for smear effect of high light target in space observation image, an automatic de-smear system was established, and its applied algorithms such as Gaussian noise distribution parameters estimation of image background, target smear detection and image gray-scale value correction were investigated. First, the Gaussian noise-s distribution parameter of star observation image was estimated with histogram least square curve fitting. Subsequently, utilizing the smear features in observation image, a smear detection algorithm based on statistical information was proposed. Then, after the smear position was determined, the contaminated pixel-s gray-scale value was corrected. Finally, a set of de-smearing system in star observation image was with Visual Studio 2005. Experimental results indicate that with the star observation image of 16 bit and 1 0241 024 pixel, the processing time of single frame image is about 300 ms. The smear effect is well corrected, and the useful information of stars and target is not destroyed. The processed image by our algorithm can satisfy the demands of stability, reliability and precision for dim target detection in space observation image.
- signal and information processing /
- smear effect /
- least square curve fitting /
- gray-scale correction /
- gradient variable

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参考文献(1)

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