基于最大检测概率的可见光与SAR图像融合方法

EO and SAR Image Fusion Algorithm Based on Maximum Detection Probability

针对侦察及制导领域中利用多源图像提高目标检测概率的问题,文中提出一种基于最大检测概率的可见光与SAR图像融合方法。在该方法中,通过反馈学习的方法,建立融合图像检测概率与各指标之间的关系,从而挖掘出与检测概率具有强相关性的指标,并在此基础上自适应获取在融合图像具有最大检测概率条件下的异源图像加权系数。仿真结果验证了该方法的有效性。

Due to the problem of increasing the target detection probability using multi-source image fusion for reconnaissance and guidance,an EO and SAR image fusion algorithm based on maximum detection probability has been proposed in this paper. It builds the relationship between the detection probability and each indicator of fusion image using the feedback learning method,then finds the indicator which has strong relativity with the detection probability,and self-adaptively obtains the weighted coefficients of multi-source images. By using these weighted coefficients,the fusion image has the maximum detection probability. It indicates the validity of this method at simulation.