多源红外弱小目标灰色关联融合识别方法

针对从复杂地物背景下识别红外弱小目标的需求,提出了一种针对中/长波红外图像的多源信息融合识别方法。首先在对低信噪比红外图像的预处理中改进了去相关和分块阈值分割等算法以抑制温度场的非线性影响,有效提取出目标及其特征,再利用基于灰色理论的目标关联度计算得到基本概率赋值,进一步运用D-S证据理论组合规则对多个观测样本的信任度进行决策融合,得到同一时刻多传感器探测样本数据的最终识别结果。实验表明,该方法对复杂地物背景下的红外弱小目标具有较高的识别效率。

Fusion recognition based on grey relativity for multi-source infrared dim target

Aiming at the identification of infrared dim targets from complex background,a multi-source information fusion recognition method for medium-wave and long-wave infrared images is proposed. Firstly,during the preprocessing of infrared images with low signal-to-noise ratio,an improved method for decorrelation and block threshold segmentation is proposed to suppress the nonlinear influence of the temperature field,extract the target and its characteristics effectively. Then the target relativity based on the grey theory is calculated and assigned the basic probability and Dempster-Shafer evidence theory based combination rule is used to fuse the confidence of multiple observation samples. The final recognition results are obtained from the simultaneous data of the multi-sensors. Experiments show that the method has high recognition efficiency for the dim small targets under the complex background.