Unsupervised Change Detection From Heterogeneous Data Based on Image Translation

• Published in: IEEE transactions on geoscience and remote sensing Vol. 60; pp. 1 - 13
• Main Authors: Liu, Zhun-Ga, Zhang, Zuo-Wei, Pan, Quan, Ning, Liang-Bo
• Format: Journal Article
• Language: English
• Published: New York IEEE 2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Change detection; Classification; Classifiers; Clustering; Detection; Feature extraction; heterogeneous images; image translation; Laser radar; Object recognition; Optical imaging; Optical properties; Optical sensors; Pixels; Radar polarimetry; Remote sensing; Remote sensors; SAR (radar); Synthetic aperture radar; Translation; unsupervised change detection (USCD)

It is quite an important and challenging problem for change detection (CD) from heterogeneous remote sensing images. The images obtained from different sensors (i.e., synthetic aperture radar (SAR) & optical camera) characterize the distinct properties of objects. Thus, it is impossible to detec...