Method for carrying out change detection on remote sensing images based on treelet fusion and level set segmentation

Abstract

The invention discloses a method for carrying out change detection on remote sensing images based on treelet fusion and level set segmentation, and mainly solves the problem that much pseudo-change information exists in the existing change detection methods. The method is implemented through the following steps: inputting two time-phase remote sensing images, then respectively carrying out mean shift filtering on each image so as to obtain two time-phase filtered images; respectively carrying out two-dimensional stationary wavelet decomposition on the two time-phase filtered images three times under different level numbers; carrying out subtraction on wavelet coefficient matrixes of corresponding directional son-bands of the filtered images with the same decomposition level number; carrying out enhancement and two-dimensional wavelet inverse transformation reconstruction on wavelet coefficient difference matrixes in horizontal and vertical directions by using a sobel operator; and fusing the reconstruction images with different decomposition level numbers so as to obtain a final difference map by using a treelet algorithm, then carrying out level set segmentation on the differencemap so as to obtain a change detection result. By using the method disclosed by the invention, the accuracy of the change detection result can be improved effectively, and the edge feature of a change area can be maintained better, therefore, the method can be applied to the fields of natural disaster analysis, land resource monitoring, and the like.

Description

technical field [0001] The invention belongs to the technical field of image processing, and specifically relates to a remote sensing image change detection method based on treelet fusion and level set segmentation, which can be used for remote sensing image analysis in many fields such as land resource monitoring, natural disaster analysis, and urban development planning. Background technique [0002] Remote sensing image change detection technology is an important part of remote sensing image research. It compares and analyzes the images of the same place in different periods, and obtains the information of surface changes that people need according to the differences between the images. [0003] In the change detection method of remote sensing images, the simplest and most common method is to directly differentiate the gray value of the image to obtain the difference image, and use the threshold to distinguish the change class from the non-change class. However, due to fa...

AI Technical Summary

Problems solved by technology

Due to the down-sampling characteristics of the dual-tree complex wavelet transform, this method first needs to interpolate the original image, and the choice of interpolation method has a certain impact on the result. In addition, it is easy to accumulate classification errors when dividing the low-frequency coefficient matrix and high-frequency coefficient matrix separately. Also affects the accuracy of change detection results

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