CAJ | 학술논문

鉴于传统的基于单幅图像奇异值分解红外弱小目标检测算法的不足，提出了一种新的基于图像序列奇异值分解的红外弱小目标检测算法。首先，利用图像序列构造图像矩阵并进行奇异值分解，得到对应的特征值与特征向量；其次，利用处理后的特征值和特征向量重构图像序列，得到新的特征图像序列；再次，在特征图像序列中选取合适的特征图像进行处理从而增强目标并抑制背景；然后，对新特征图像进行阈值分割，得到要检测的弱小目标；最后，对序列中的每幅图像分别进行帧间位置修正与帧内位置修正，以达到检测红外弱小目标的目的。实验结果表明该算法具有很好的鲁棒性与实时性。
감우전통적기우단폭도상기이치분해홍외약소목표검측산법적불족，제출료일충신적기우도상서렬기이치분해적홍외약소목표검측산법。수선，이용도상서렬구조도상구진병진행기이치분해，득도대응적특정치여특정향량；기차，이용처리후적특정치화특정향량중구도상서렬，득도신적특정도상서렬；재차，재특정도상서렬중선취합괄적특정도상진행처리종이증강목표병억제배경；연후，대신특정도상진행역치분할，득도요검측적약소목표；최후，대서렬중적매폭도상분별진행정간위치수정여정내위치수정，이체도검측홍외약소목표적목적。실험결과표명해산법구유흔호적로봉성여실시성。
Considering the shortage of conventional single-image-SVD-based infrared dim and small target detection method, a new sequential-image-SVD-based method is proposed in this paper. Firstly, an image matrix is constructed upon sequential images and then decomposed by the SVD algorithm, and consequently the corresponding singular values and singular vectors are achieved. Secondly, new sequential feature images are reconstructed by using processed singular values and singular vectors. Thirdly, the selected feature images from sequential feature images are further processed to enhance the small targets and suppress the clutter background. Fourthly, the small targets are obtained by segmenting feature images. Finally, the detection task of small target detection is completed by refining the inter-frame and intra-frame target locations. Experimental results show that the proposed algorithm is robust and with real-time e?ciency.