TY - GEN
T1 - Fine geometric alignment of very high resolution optical images using registration noise and quadtree structure
AU - Han, Youkyung
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/12/1
Y1 - 2017/12/1
N2 - Very High Resolution (VHR) multitemporal images that have been already applied registration process still show a residual misalignment due to the dissimilarities of the acquisition environment. The objective of this paper is to mitigate the residual misalignment between VHR images to get a fine geometric alignment result. Here we propose to refine the local misalignment between VHR images by extracting Registration Noise (RN), which is denoted as misaligned samples. Extracted RN pixels are used as Control Points (CPs), and local distribution analysis of the CPs in a specific region defined by a quadtree structure is carried out for finding their correspondences. Matched CP pairs are employed for generating a deformation map to warp the sensed image to the master image. Experiments carried out on both simulated and real multitemporal VHR datasets acquired from IKONOS and QuickBird sensors confirm the validity of the analysis of the proposed method.
AB - Very High Resolution (VHR) multitemporal images that have been already applied registration process still show a residual misalignment due to the dissimilarities of the acquisition environment. The objective of this paper is to mitigate the residual misalignment between VHR images to get a fine geometric alignment result. Here we propose to refine the local misalignment between VHR images by extracting Registration Noise (RN), which is denoted as misaligned samples. Extracted RN pixels are used as Control Points (CPs), and local distribution analysis of the CPs in a specific region defined by a quadtree structure is carried out for finding their correspondences. Matched CP pairs are employed for generating a deformation map to warp the sensed image to the master image. Experiments carried out on both simulated and real multitemporal VHR datasets acquired from IKONOS and QuickBird sensors confirm the validity of the analysis of the proposed method.
KW - Fine geometric alignment
KW - Quadtree structure
KW - Registration noise
KW - Very high resolution images
UR - https://www.scopus.com/pages/publications/85041828088
U2 - 10.1109/IGARSS.2017.8127925
DO - 10.1109/IGARSS.2017.8127925
M3 - Conference contribution
AN - SCOPUS:85041828088
T3 - International Geoscience and Remote Sensing Symposium (IGARSS)
SP - 4189
EP - 4192
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 -