CAJ | 학술논문

提出一种基于岭回归协助稀疏表示的红外小目标检测方法。该方法分别采用二维高斯模型和正态分布随机矩阵生成红外小目标样本和背景样本，继而建立超完备字典。红外小目标检测包括两个阶段，在第一阶段利用岭回归表示快速计算所有测试样本的岭回归重建误差；在第二阶段，根据岭回归重建误差自适应选择候选目标，并计算其稀疏表示重建误差实现目标检测。对提出的方法进行了实验验证，结果表明：提出的方法具有较快的速度和较强的鲁棒性。
제출일충기우령회귀협조희소표시적홍외소목표검측방법。해방법분별채용이유고사모형화정태분포수궤구진생성홍외소목표양본화배경양본，계이건립초완비자전。홍외소목표검측포괄량개계단，재제일계단이용령회귀표시쾌속계산소유측시양본적령회귀중건오차；재제이계단，근거령회귀중건오차자괄응선택후선목표，병계산기희소표시중건오차실현목표검측。대제출적방법진행료실험험증，결과표명：제출적방법구유교쾌적속도화교강적로봉성。
An infrared small target detection method is proposed based on sparse representation assisted by ridge regression. The proposed method constructs over-complete dictionary with target samples and background samples which are produced by two-dimensional Gaussian model and normal random matrix respectively. Infrared small target detection consists of two stages. In the first stage, the construction errors of detect samples are calculated fast using ridge regression. In the second stage, candidate samples are selected adaptively by ridge regression reconstruction errors, and infrared small targets are detected with the reconstruction errors of the candidate samples selected which are computed with sparse representation. The experimental results on several infrared images show that the proposed method is faster and more robust than the existing methods.