关键词: 变化检测, 特征优选, 直方图相交, 面向对象

Abstract: Though analyzing problem of object-oriented change detection for high-resolution remote sensing image, performance of change detection will be improved by following selection and utilization of multi-feature on image’s object. An unsupervised method to select optimal feature of image’s object for change detection has been put forward. Firstly, getting image’s objects through object-oriented segmentation algorithm and forming the feature images, then acquiring results of change detection with optimal feature images on the basis of rules to eliminate redundancy from data utmostly, finally, compared with information of change intensity in the reference result through histogram cross, and get the optimal feature according to the comparing result. At last, achieve the fusion result of multi-feature using the MRF model automatically. New algorithm realizes better automatic optimal selection and integrated utilization of multi-feature, validation results show new algorithm has very good accuracy and robustness.

Key words: change detection, optimal selection of feature, histogram cross, object-oriented