小面元匹配与熵权重在红外假目标评价中的运用  

Application of Small Patch Registration and Entropy Power in the Evaluation of Infrared Decoy

作　　者：陈亦望[1] 张品[1] 秦建飞[1] 李晓光[1] 

机构地区：[1]解放军理工大学工程兵工程学院,江苏南京210007

出　　处：《红外》2007年第3期14-19,共6页Infrared

摘　　要：提出了一种运用小面元匹配和熵权重评价假目标红外特征的方法。该方法利用小面元法合理地分割选取目标图像的部分信患,通过计算真假目标多图像匹配概率并利用熵权重确定评价标准,评价假目标的示假效果。两者匹配的概率值越高,说明假目标的示假效果越好,反之越差。实验证明,该方法能够很好地消除图像信息提取中的误差。A method for evaluating the infrared signatures of decoys by using small patches and entropy is proposed. Firstly, a small patch method is used to segment the image patches with high values, then the image matching probability is calculated and the evaluation standard is determined by using entropy, and finally the effectiveness of the decoy is evaluated. The higher the matching probability between the real target and the decoy is, the greater the similarity of them is and the better the effectiveness of the decoy is. This method can eleminate the error in image information extraction very well.

关 键 词：假目标 红外 小面元 图像匹配 

分 类 号：TN219[电子电信—物理电子学]