DETECTING CHANGES IN HIGH RESOLUTION REMOTE SENSING IMAGES USING SUPERPIXELS

In this paper, in order to detect changes in high resolution remote sensing images, we propose an MRF-based change detection method combined with the semantic information. Two temporal high resolution remote sensing images are represented by features of superpixels. For given images, we transform the change detection problem into a binary classification problem by combining differences in both low-level features and semantic information in MRF smoothing framework. All pixels are divided into two categories: changed or unchanged, so we can extract change information from classification result. Experimental results of two Geo-Eye1 high-resolution remote sensing images at different time demonstrate the efficiency of this proposed method. Detection combined with semantic information can significantly improve the result than only with low-level features. Adding Markov smoothing can also improve the detection results slightly.