| 题名: | Auto-focusing technology for photoelectric measurement system |
| 作者: | LEi Tao; Yang Sihan; Zhang Yong; Wu Qinzhang
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| 出版日期: | 2009
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| 会议名称: | Proceedings of SPIE
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| 会议日期: | 2009
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| 通讯作者: | LEi Tao
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| 中文摘要: | Automatic focusing (AF) is a key technology of measuring TV capturing the clear objective image in photoelectric measurement system. It is viable to enhance the performance of measuring TV through focusing effectively and quickly. In the process of maneuvering target tracking, the background and the feature of targets change from time to time, and the reliability of AF is highly required. Firstly, conditions for starting AF need to be investigated. The relation between degree of definition and edge acutance is proved by experiments. Combined with the sharpness value, it decides whether to begin AF. Secondly, it needs focusing quickly and exactly after starting AF. The accuracy and efficiency of the sharpness function is another key factor of AF. By comparing some favorable sharpness functions, normalized variance and square-gradient functions are employed based on focus windows. Thirdly, the optimized mountain-climb searching algorithm based on the defocusing extents and the adaptive searching step size is proposed. Experiments show the algorithm proposed improves the speed and reliability of AF. |
| 英文摘要: | Automatic focusing (AF) is a key technology of measuring TV capturing the clear objective image in photoelectric measurement system. It is viable to enhance the performance of measuring TV through focusing effectively and quickly. In the process of maneuvering target tracking, the background and the feature of targets change from time to time, and the reliability of AF is highly required. Firstly, conditions for starting AF need to be investigated. The relation between degree of definition and edge acutance is proved by experiments. Combined with the sharpness value, it decides whether to begin AF. Secondly, it needs focusing quickly and exactly after starting AF. The accuracy and efficiency of the sharpness function is another key factor of AF. By comparing some favorable sharpness functions, normalized variance and square-gradient functions are employed based on focus windows. Thirdly, the optimized mountain-climb searching algorithm based on the defocusing extents and the adaptive searching step size is proposed. Experiments show the algorithm proposed improves the speed and reliability of AF. |
| 收录类别: | Ei
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| 语种: | 英语
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| 卷号: | 7383
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| 文章类型: | 会议论文
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| 内容类型: | 会议论文
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| URI标识: | http://ir.ioe.ac.cn/handle/181551/7505
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| Appears in Collections: | 光电探测技术研究室（三室）_会议论文
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| 2009-174.pdf（291KB） | 会议论文 | -- | 限制开放 | | View
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| Recommended Citation: | |
LEi Tao,Yang Sihan,Zhang Yong,et al. Auto-focusing technology for photoelectric measurement system[C]. 见:Proceedings of SPIE. 2009.
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