基于红外图像和特征融合的飞机目标识别方法

Aircraft Target Identification Based on Infrared Image and Feature Fusion

针对由于空中飞机红外图像的形状、姿态和大小的高度复杂性使得现有的红外目标识别方法的识别率和鲁棒性不高的问题,提出一种基于红外图像和特征融合的飞机红外目标识别方法。该方法充分利用尺度不变、特征变换和奇异值分解算法,提取飞机红外图像的识别特征,构造特征向量,由此进行红外目标识别。在5类飞机红外图像数据库上,对本文方法和传统方法进行对比实验,结果表明了该方法的可行性和有效性。

The high complexity of shape, attitude and size of the infrared images of the aerial aircrafts may result in low recognition rate and processing speed to the classical infrared target recognition methods. To solve the problem, we proposed a method for the aircraft target recognition based on infrared images and feature fusion. The proposed method made full use of the algorithms of scale invariant feature transform and singular value decomposition. The recognition features of infrared image were extracted at first, and then the fusion feature vector was constructed. The aircrafts were recognized by BP neural network. Based on infrared image database of five types of aircraft, we made experiments for comparision of our method with the classifical methods. The result show the effectiveness and feasibility of the method.