Open AccessObject‐based method for optical and SAR images change detection
Author(s) -
Wan Ling,
Zhang Tao,
You Hongjian
Publication year - 2019
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2019.0620
Subject(s) - artificial intelligence , computer science , computer vision , change detection , synthetic aperture radar , spurious relationship , pattern recognition (psychology) , sensitivity (control systems) , segmentation , feature (linguistics) , remote sensing , geography , linguistics , philosophy , machine learning , electronic engineering , engineering
This study introduces an automatic method for change detection of multi‐sensor remote‐sensing images (e.g. optical and synthetic aperture radar (SAR) images). As object‐based image analysis can effectively reduce the spurious changes and the sensitivity to registration, first, multi‐date segmentation is employed to generate homogeneous image objects in spectral, spatial, and temporal, in order to weak the intensity variation effects of multi‐sensor images. Then, modified fuzzy c‐means (FCM) algorithms are employed to preliminarily classify optical and SAR images, and a criterion is defined using membership values of parcels to select the sample parcels for each class and image. Finally, a change detection principle, which takes statistical properties as the feature space, is introduced to detect changes between multi‐sensor images. The experiment results verify that the proposed method is able to cope with optical and SAR images change detection.