Detecting Subpixel and Point Target by Image Accumulation

李金宗; 李宁宁

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Detecting Subpixel and Point Target by Image Accumulation

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- Detecting Subpixel and Point Target by Image Accumulation
- Acta Electronica Sinica Issue 1, (1997)
- 作者机构：
  
  哈尔滨工业大学
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP391.4
- Published：1997
- 稿件说明：
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[1]李金宗,李宁宁.图象积累与自适应门限检测技术的研究[J].电子学报,1997(01):77-79.

李金宗, 李宁宁. Detecting Subpixel and Point Target by Image Accumulation[J]. Acta Electronica Sinica, 1997, (1).
[1]李金宗,李宁宁.图象积累与自适应门限检测技术的研究[J].电子学报,1997(01):77-79. DOI：

李金宗, 李宁宁. Detecting Subpixel and Point Target by Image Accumulation[J]. Acta Electronica Sinica, 1997, (1). DOI：

摘要

为了从低分辨率和低信杂比的图象序列中检测亚象元目标和点目标，本文定义了有效积累帧数，证明了在有效积累帧数内，积累ｍ帧序列图象，积累平均图象的信杂比提高到倍．在图象积累的基础上研究自适应门限检测技术，定义了最小错误率规则，并且导出了初始门限以及概率参数的计算公式．为了进一步降低虚警，还建立了后处理的方案，实验结果证实了理论分析的正确性．

Abstract

The number of effective accumulated frames （NEAF） is defined in this paper. It is proved that SNR in the average accumulated image is increased by M times within NEAF. Further

the techniques of adaptable threshold detection are studied based on image accumulation. the rule of minimal errer probabi lity （ROMEP） is defined and the equation of initlal threshold and the detection probability

false alarm probability as well as error probability are deduced under this rule. The post-processing project is also set up so as to decrease still further false alarm.

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