红外与毫米波学报2019，Vol.38Issue(5)：578-586,9.DOI:10.11972/j.issn.1001-9014.2019.05.006
基于稀疏表示的红外空中目标分类算法
Rotation-invariant infrared aerial target identification based on SRC
摘要
Abstract
Aircraft identification is implemented on thermal images acquired from ground-to-air infrared cameras.SRC is proved to be an effective image classifier robust to noise,which is quite suitable for thermal image tasks.However,rotation invariance is challenging requirements in this task.To solve this issue,a method is proposed to compute the target main orientation firstly,then rotate the target to a reference direction.Secondly,an over-complete dictionary is learned from histogram of oriented gradient features of these rotated targets.Thirdly,a sparse representation model is introduced and the identification problem is converted to a l1-minimization problem.Finally,different aircraft types are predicted based on an evaluation index,which is called residual error.To validate the aircraft identification method,a recorded infrared aircraft dataset is implemented in an airfield.Experimental results show that the proposed method achieves 98.3％ accuracy,and recovers the identity beyond 80％ accuracy even when the test images are corrupted at 50％.关键词
红外图像/空中目标/旋转不变性/稀疏表示分类Key words
infrared image/aircraft identification/rotation invariant/sparse representation classification分类
信息技术与安全科学引用本文复制引用
金璐,李范鸣,刘士建,王霄..基于稀疏表示的红外空中目标分类算法[J].红外与毫米波学报,2019,38(5):578-586,9.基金项目
Supported by the Thirteen Five National Defense Research Foundation (Jzx2016-0404/Y72-2) （Jzx2016-0404/Y72-2）
Shanghai Key Laboratory of Criminal Scene Evidence funded Foundation (2017xcwzk08). （2017xcwzk08）
