TY - GEN
T1 - Infrared Small Target Detection Based on Morphological Feature Extraction
AU - Zhao, Mingjing
AU - Li, Lu
AU - Li, Wei
AU - Li, Liwei
AU - Zhang, Wenjuan
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/7
Y1 - 2019/7
N2 - Infrared (IR) small target detection of low signal-to-noise ratio (SNR) is a very meaningful and challenging subject in detecting and tracking system. Therefore, an effective method is proposed in this paper. First of all, a morphological feature extraction method is used to reconstruct a new image that the small target is disappeared, then the original image and the reconstruction image are made difference as preprocessed image. In this way, important spatial information can be extracted well in IR image. Then, a low-rank and sparse decomposition method is employed to obtain the background image and the target image respectively, the target separation can be enhanced and the background clutter can be suppressed simultaneously. Finally, the obtained target image is segmented by a simple adaptive segmentation method. The experimental results indicate that the proposed method is of great improvement compared with several existing methods, what's more, it can achieve the highest SNR among these methods.
AB - Infrared (IR) small target detection of low signal-to-noise ratio (SNR) is a very meaningful and challenging subject in detecting and tracking system. Therefore, an effective method is proposed in this paper. First of all, a morphological feature extraction method is used to reconstruct a new image that the small target is disappeared, then the original image and the reconstruction image are made difference as preprocessed image. In this way, important spatial information can be extracted well in IR image. Then, a low-rank and sparse decomposition method is employed to obtain the background image and the target image respectively, the target separation can be enhanced and the background clutter can be suppressed simultaneously. Finally, the obtained target image is segmented by a simple adaptive segmentation method. The experimental results indicate that the proposed method is of great improvement compared with several existing methods, what's more, it can achieve the highest SNR among these methods.
KW - Infrared (IR) Image
KW - Morphology Feature Extraction
KW - Sparse and Low-rank Decomposition
KW - Target Detection
UR - http://www.scopus.com/inward/record.url?scp=85077680395&partnerID=8YFLogxK
U2 - 10.1109/IGARSS.2019.8898046
DO - 10.1109/IGARSS.2019.8898046
M3 - Conference contribution
AN - SCOPUS:85077680395
T3 - International Geoscience and Remote Sensing Symposium (IGARSS)
SP - 1398
EP - 1401
BT - 2019 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 39th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019
Y2 - 28 July 2019 through 2 August 2019
ER -