基于核稀疏编码的红外目标识别方法

杨春伟; 王仕成; 廖守亿; 刘华平

红外技术, 2016, 38 (3): 230, 网络出版: 2016-10-19

基于核稀疏编码的红外目标识别方法

An Infrared Target Recognition Method Based on Kernel Sparse Coding

论文大纲

杨春伟 ^1,2,*王仕成 ¹廖守亿 ¹刘华平 ²

作者单位

¹ 第二炮兵工程大学精确制导仿真技术实验室，陕西西安 710025

² 清华大学计算机科学与技术系，北京 100084

协方差描述子核稀疏编码红外目标识别 covariance descriptor kernel sparse coding infrared target recognition

摘要

针对红外目标识别问题，提出了一种基于协方差描述子和核稀疏编码的红外目标识别方法。该方法结合了红外图像的灰度、一阶以及二阶梯度等特征的协方差描述子作为红外目标的特征，并采用 Log-Euclidean度量进行特征相似性计算，通过高斯核函数将协方差描述子映射到高维空间，最后在新的特征空间上进行稀疏编码。实测数据实验结果表明，与传统的 KNN（k-nearest neighbor，k最近邻）以及 SVM（support vector machine，支持向量机）等分类算法相比，基于核稀疏编码的红外识别方法在识别准确率上有很大的提高。

Abstract

An infrared target recognition method based on covariance descriptor and kernel sparse coding isproposed in this paper. Covariance descriptor combining infrared image gray intensity values and the normof first and second order derivatives of the intensities as infrared image features. With respect to x and y isextracted as feature representation, similarity of covariance descriptors is computed through Log-Euclideanmetric. Then covariance descriptors are mapped into a high dimensional feature space through Gaussiankernel function. Finally, infrared target recognition is accomplished using sparse coding in the new featurespace. Experiments on the real infrared images show that our method obtains better results compared withtraditional algorithms such as KNN and SVM.

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杨春伟, 王仕成, 廖守亿, 刘华平. 基于核稀疏编码的红外目标识别方法[J]. 红外技术, 2016, 38(3): 230. YANG Chunwei, WANG Shicheng, LIAO Shouyi, LIU Huaping. An Infrared Target Recognition Method Based on Kernel Sparse Coding[J]. Infrared Technology, 2016, 38(3): 230.

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