TY - GEN
T1 - Precise co-registration of very high resolution optical images by registration-noise estimation
AU - Han, Youkyung
AU - Bovolo, Francesca
AU - Bruzzone, Lorenzo
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/11/10
Y1 - 2015/11/10
N2 - Very High Resolution (VHR) multitemporal images show a residual misalignment even after applying effective state of the art co-registration. This residual misalignment is caused by the dissimilarities of the acquisition circumstances such as off-nadir angle of the sensor, stability of the acquisition platform, structure of the considered scene, and so on. This paper aims at mitigating the residual misalignment of VHR multitemporal images to get a fine co-registration result. Here we propose to use Registration Noise (RN), which represents misaligned samples, for refining co-registration. After standard co-registration, a local analysis of RN pixels is fulfilled for extracting Control Points (CPs) and matching them according to the amount of the RN pixels. Matched CPs are employed for generating a deformation map to warp one image to the other image. Experiments carried out on both simulated and real multitemporal VHR images acquired by QuickBird sensors confirm the validity of the analysis and effectiveness of the proposed method.
AB - Very High Resolution (VHR) multitemporal images show a residual misalignment even after applying effective state of the art co-registration. This residual misalignment is caused by the dissimilarities of the acquisition circumstances such as off-nadir angle of the sensor, stability of the acquisition platform, structure of the considered scene, and so on. This paper aims at mitigating the residual misalignment of VHR multitemporal images to get a fine co-registration result. Here we propose to use Registration Noise (RN), which represents misaligned samples, for refining co-registration. After standard co-registration, a local analysis of RN pixels is fulfilled for extracting Control Points (CPs) and matching them according to the amount of the RN pixels. Matched CPs are employed for generating a deformation map to warp one image to the other image. Experiments carried out on both simulated and real multitemporal VHR images acquired by QuickBird sensors confirm the validity of the analysis and effectiveness of the proposed method.
KW - change vector analysis
KW - image co-registration
KW - Registration noise
KW - very high resolution images
UR - http://www.scopus.com/inward/record.url?scp=84962617127&partnerID=8YFLogxK
U2 - 10.1109/IGARSS.2015.7326760
DO - 10.1109/IGARSS.2015.7326760
M3 - Conference contribution
AN - SCOPUS:84962617127
T3 - International Geoscience and Remote Sensing Symposium (IGARSS)
SP - 4232
EP - 4235
BT - 2015 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015
Y2 - 26 July 2015 through 31 July 2015
ER -