TY - GEN
T1 - Iterative anomaly detection
AU - Wang, Yulei
AU - Xue, Bai
AU - Wang, Lin
AU - Li, Hsiao Chi
AU - Lee, Li Chien
AU - Yu, Chunyan
AU - Song, Meiping
AU - Li, Sen
AU - Chang, Chein I.
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/12/1
Y1 - 2017/12/1
N2 - Anomaly detection (AD) is designed to find targets that are spectrally distinct from their surrounding neighborhood. Unfortunately, commonly used anomaly detectors generally do not take into account its surrounding spatial information. This paper derives an iterative version of anomaly detection, iterative anomaly detection (IAD) to address this issue. Its idea is to use a Gaussian filter to capture spatial information of the anomaly detection map and then feeds back the Gaussian filtered AD map to create a new data cube. The whole process is repeated over again in an iterative manner. When IAD is terminated anomaly representatives are identified and can be used as desired target signatures to implement constrain energy minimization (CEM) so as to classify all detected anomalies. Accordingly, IAD can be considered as anomaly classification.
AB - Anomaly detection (AD) is designed to find targets that are spectrally distinct from their surrounding neighborhood. Unfortunately, commonly used anomaly detectors generally do not take into account its surrounding spatial information. This paper derives an iterative version of anomaly detection, iterative anomaly detection (IAD) to address this issue. Its idea is to use a Gaussian filter to capture spatial information of the anomaly detection map and then feeds back the Gaussian filtered AD map to create a new data cube. The whole process is repeated over again in an iterative manner. When IAD is terminated anomaly representatives are identified and can be used as desired target signatures to implement constrain energy minimization (CEM) so as to classify all detected anomalies. Accordingly, IAD can be considered as anomaly classification.
UR - http://www.scopus.com/inward/record.url?scp=85041805007&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85041805007&partnerID=8YFLogxK
U2 - 10.1109/IGARSS.2017.8127021
DO - 10.1109/IGARSS.2017.8127021
M3 - Conference contribution
AN - SCOPUS:85041805007
T3 - International Geoscience and Remote Sensing Symposium (IGARSS)
SP - 586
EP - 589
BT - 2017 IEEE International Geoscience and Remote Sensing Symposium
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 37th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2017
Y2 - 23 July 2017 through 28 July 2017
ER -