Remote sensing image change detection method based on fusion and PCA kernel fuzzy clustering

Abstract

The invention discloses a remote sensing image change detection method based on fusion and PCA kernel fuzzy clustering. The remote sensing image change detection method mainly solves the problems that in the prior art, the detection effect is not ideal, the accuracy of single-type difference image detection is low, and the application range is narrow. The method comprises the steps: (1) inputting two time phase remote sensing images X1 and X2 and conducting median filtering; (2) calculating a differential image, a logarithmic specific value image and a mean value ratio image of the two images after the filtering; (3) conducting fusion on the three images to obtain an image Xd after the fusion; (4) using a PCA method for conducting feature extraction on the images after the fusion, and obtaining a feature vector of each pixel to form a feature space matrix; (5) using a kernel-based fuzzy C mean value method for clustering the feature space matrix into two classes; (6) obtaining a final change detection result image according to the clustering result. The remote sensing change detection method has the better anti-noise performance and detection accuracy, the better effects of remote sensing images of different types can be obtained, and the remote sensing image change detection method can be applied to the field of environment monitoring and disaster evaluation.

Description

technical field [0001] The invention belongs to the technical field of image processing, relates to a remote sensing image change detection method, and can be used in the fields of urban planning, natural disaster assessment, dynamic monitoring of land use and land cover, and the like. Background technique [0002] Remote sensing image change detection refers to the comparison and analysis of two or more images of the same area in different periods, and the change information of ground objects is obtained according to the differences between the images. Remote sensing image change detection technology has been successfully applied in many fields, such as environmental monitoring, dynamic monitoring of land use and land cover, forest or vegetation change analysis, disaster assessment, agricultural survey, urban change research and artificial target monitoring in the military and ground armed deployment analysis. [0003] The remote sensing image change detection method mainl...

AI Technical Summary

Problems solved by technology

[0007] The purpose of the present invention is to propose a remote sensing image change detection method based on fusion and PCA kernel fuzzy clustering. With the existing technology, the detection effect is not ideal, the detection accuracy of a single type of difference map is low, and the scope of application is narrow, so as to better detect change area

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