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基于改进的局部反熵算子的小目标检测

邓鹤1，魏艳涛1，童名文1，瞿少成2   

  1. 1. 华中师范大学 信息与新闻传播学院，湖北 武汉 430079；2. 华中师范大学 物理科学与技术学院，湖北 武汉 430079
  • 出版日期:2013-04-25 发布日期:2013-04-15
  • 基金资助:
    国家自然科学基金资助项目（61074046）；教育部人文社科基金资助项目（10YJC880113）；湖北省自然科学基金资助项目（2011CDB163）；中央高校基本科研业务费基金资助项目（CCNU120002040471，CCNU10C01003）；华中师范大学科研启动基金资助项目（CCNU12T03040）

Small target detection based on modified local reverse entropy operator

  • Online:2013-04-25 Published:2013-04-15
  • Supported by:
    The National Natural Science Foundation of China (61074046); The Ministry of Education of Humanities and Social Science Project (10YJC880113); The Nature Science Foundation of Hubei Province (2011CDB163); Fundamental Research Funds for the Central Universities (CCNU120002040471, CCNU10C01003); Scientific Research Starting Foundation of Central China Normal University (CCNU12T03040)

被引次数

3

摘要： 利用小目标的出现会导致局部反熵值发生较大变化这一特性，提出了基于改进的局部反熵算子和改进的区域生长技术的小目标检测新方法。该方法首先利用改进的局部反熵算子构建局部反熵图抑制小目标图像背景，然后采用改进的区域生长技术有效地检测小目标。仿真实验结果表明，所提出的方法能快速和准确地检测出复杂背景下的小目标。

Abstract: A small-target detection approach was proposed, which is based on the modified local reverse entropy operator and the improved region growing technology. The approach adopted the fact that the emergence of small target could lead to the large change of local reverse entropy. The proposed approach made use of the local reverse entropy map to suppress the small-target image background, and then adopted the improved region growing technique to effectively detect small targets. Experimental results show that the proposed approach can detect small targets accurately and quickly.

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