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题名:
Optimum threshold selection method of centroid computation for Gaussian spot
作者: Li, Xuxu1,2; Li, Xinyang1; Wang, Caixia1
出版日期: 2015
会议名称: Proceedings of SPIE - The International Society for Optical Engineering
会议日期: 2015
学科分类: Computational complexity - Error detection - Gaussian distribution - Image analysis - Image processing - Optical data processing - Parallel processing systems - Target tracking - Wavefronts
DOI: 10.1117/12.2199247
通讯作者: Li, Xuxu (lixuxu188@163.com)
中文摘要: Centroid computation of Gaussian spot is often conducted to get the exact position of a target or to measure wave-front slopes in the fields of target tracking and wave-front sensing. Center of Gravity (CoG) is the most traditional method of centroid computation, known as its low algorithmic complexity. However both electronic noise from the detector and photonic noise from the environment reduces its accuracy. In order to improve the accuracy, thresholding is unavoidable before centroid computation, and optimum threshold need to be selected. In this paper, the model of Gaussian spot is established to analyze the performance of optimum threshold under different Signal-to-Noise Ratio (SNR) conditions. Besides, two optimum threshold selection methods are introduced: TmCoG (using m % of the maximum intensity of spot as threshold), and TkCoG (usingμn+κσ n as the threshold), μnand σnare the mean value and deviation of back noise. Firstly, their impact on the detection error under various SNR conditions is simulated respectively to find the way to decide the value of k or m. Then, a comparison between them is made. According to the simulation result, TmCoG is superior over TkCoG for the accuracy of selected threshold, and detection error is also lower. © Copyright 2015 SPIE.
英文摘要: Centroid computation of Gaussian spot is often conducted to get the exact position of a target or to measure wave-front slopes in the fields of target tracking and wave-front sensing. Center of Gravity (CoG) is the most traditional method of centroid computation, known as its low algorithmic complexity. However both electronic noise from the detector and photonic noise from the environment reduces its accuracy. In order to improve the accuracy, thresholding is unavoidable before centroid computation, and optimum threshold need to be selected. In this paper, the model of Gaussian spot is established to analyze the performance of optimum threshold under different Signal-to-Noise Ratio (SNR) conditions. Besides, two optimum threshold selection methods are introduced: TmCoG (using m % of the maximum intensity of spot as threshold), and TkCoG (usingμn+κσ n as the threshold), μnand σnare the mean value and deviation of back noise. Firstly, their impact on the detection error under various SNR conditions is simulated respectively to find the way to decide the value of k or m. Then, a comparison between them is made. According to the simulation result, TmCoG is superior over TkCoG for the accuracy of selected threshold, and detection error is also lower. © Copyright 2015 SPIE.
收录类别: SCI ; Ei
语种: 英语
卷号: 9675
ISSN号: 0277-786X
文章类型: 会议论文
页码: 967517
Citation statistics:
内容类型: 会议论文
URI标识: http://ir.ioe.ac.cn/handle/181551/7834
Appears in Collections:自适应光学技术研究室(八室)_会议论文

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作者单位: 1. Key Laboratory on Adaptive Optics, Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu, China
2. University of Chinese Academy of Sciences, Beijing, China

Recommended Citation:
Li, Xuxu,Li, Xinyang,Wang, Caixia. Optimum threshold selection method of centroid computation for Gaussian spot[C]. 见:Proceedings of SPIE - The International Society for Optical Engineering. 2015.
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