TY - JOUR
T1 - New target detection algorithm based on grayscale level connectivity in flir image sequences
AU - Hu, Xin
AU - Tang, Shuo
PY - 2007/6
Y1 - 2007/6
N2 - Aim. The level-k component zone of grayscale level connectivity was only mentioned in Ref.4 by Braga-Neto et al. Braga-Neto et al proposed a method of target detection in forward-looking infrared (FLIR) image sequences without using level-k component zone[6]. We now propose a new target detection algorithm based on extracting the level-k component zone of target in FLIR image sequences. In the full paper, we explain the new target detection algorithm in detail. In this abstract, we just add some pertinent remarks to listing the two topics of explanation. The first topic is: the grayscale level connectivity on complete lattice. In the first topic, we discuss three questions: (1) the level-k connectivity, (2) the algorithm based on grayscale level connectivity and (3) the algorithm for extracting level-k component zone of target. The second topic is; the detection of target in FLIR image sequences. In the second topic, we discuss intraframe and interframe processing. In intraframe processing, as explained in the full paper, we give a three-step procedure for detecting target in a single FLIR image. In interframe processing, target association and detection is implemented in terms of a dilation-based connectivity along the time direction in FLIR image sequences. Experimental results are given in a table in the full paper. These results indicate that using our new target detection algorithm raises the value of SNR to, on an average, 5.9 times that of the SNR previously obtained. These results demonstrate the effectiveness and robustness of the proposed method for dim target detection in the clutter and noise background.
AB - Aim. The level-k component zone of grayscale level connectivity was only mentioned in Ref.4 by Braga-Neto et al. Braga-Neto et al proposed a method of target detection in forward-looking infrared (FLIR) image sequences without using level-k component zone[6]. We now propose a new target detection algorithm based on extracting the level-k component zone of target in FLIR image sequences. In the full paper, we explain the new target detection algorithm in detail. In this abstract, we just add some pertinent remarks to listing the two topics of explanation. The first topic is: the grayscale level connectivity on complete lattice. In the first topic, we discuss three questions: (1) the level-k connectivity, (2) the algorithm based on grayscale level connectivity and (3) the algorithm for extracting level-k component zone of target. The second topic is; the detection of target in FLIR image sequences. In the second topic, we discuss intraframe and interframe processing. In intraframe processing, as explained in the full paper, we give a three-step procedure for detecting target in a single FLIR image. In interframe processing, target association and detection is implemented in terms of a dilation-based connectivity along the time direction in FLIR image sequences. Experimental results are given in a table in the full paper. These results indicate that using our new target detection algorithm raises the value of SNR to, on an average, 5.9 times that of the SNR previously obtained. These results demonstrate the effectiveness and robustness of the proposed method for dim target detection in the clutter and noise background.
KW - Complete lattice
KW - Grayscale level connectivity
KW - Infrared (IR) target detection
KW - Level-k component zone
UR - http://www.scopus.com/inward/record.url?scp=34547637649&partnerID=8YFLogxK
M3 - 文章
AN - SCOPUS:34547637649
SN - 1000-2758
VL - 25
SP - 406
EP - 410
JO - Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University
JF - Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University
IS - 3
ER -