High resolution remote sensing image change detection based on law of cosines with box-whisker plot

Abstract

The change detection method based on multi-temporal object was implemented by chi-square test and Gaussian distribution iteration to find the changed object in the past. However, trapped in the sample data does not obey the Gaussian distribution, the detection effect is not ideal. In order to fix this problem, a method based on law of cosines with box-whisker plot is proposed. First, the feature space of different time images is constructed. Then, the law of cosines is used to calculate the change index of every object. The changed objects are identified through analyzing the change index by the box-whisker plot at last. High-resolution remote sensing images of GF-1 are used as the experimental data. The experimental results show that the correct detection accuracy and omissions rate accuracy are much better than the results of the traditional multi-temporal object based change detection.