Abstract
Abstract. In view of the traditional change detection algorithm mainly depends on the spectral information image spot, failed to effectively mining and fusion of multi-image feature detection advantage, the article borrows the ideas of object oriented analysis proposed a multi feature fusion of remote sensing image change detection algorithm. First by the multi-scale segmentation of image objects based; then calculate the various objects of color histogram and linear gradient histogram; utilizes the color distance and edge line feature distance between EMD statistical operator in different periods of the object, using the adaptive weighted method, the color feature distance and edge in a straight line distance of combination is constructed object heterogeneity. Finally, the curvature histogram analysis image spot change detection results. The experimental results show that the method can fully fuse the color and edge line features, thus improving the accuracy of the change detection.
Highlights
With the rapid development of spatial information technology, the spatial resolution, spectral resolution and temporal resolution of remote sensing images are continuously improved
How to make use of abundant feature information of high-resolution remote sensing images and suppress information interference caused by imaging conditions and natural conditions has become a hot issue in remote sensing image change detection research
In order to verify the effectiveness of the multi feature fusion algorithm, a single feature and a fixed weight algorithm are compared with the algorithm in this paper
Summary
With the rapid development of spatial information technology, the spatial resolution, spectral resolution and temporal resolution of remote sensing images are continuously improved. (2010) proposed a change detection algorithm based on texture analysis and ratio transformation, which effectively analyzes the landslide disaster information by analyzing the texture features and calculating the texture indexes; Wang R. et al (2005) put forward the line feature change detection algorithm, which obtains the change detection result by extracting the edge gradient information, compression and fitting of the image and avoids the complicated process of line matching, and has strong practicability. These algorithms above verify the validity and usability of the feature from different perspectives. Based on the above theory, the histogram curvature analysis is used to obtain the change of the spot detection result
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