Detection method for building change by multispectral image

Abstract

The invention relates to a detection method for building change by a multispectral image. The detection method comprises the step of detecting the change based on a pixel ratio method to obtain change regions of all ground objects firstly, wherein the change regions are used as a change candidate region of the building. The change detection based on building feature is carried out by using the change regions detected by using a ratio method. False detection easily occurs by adopting one feature, so according to the method, feature change detection is carried out by adopting a mode of sequentially combining texture feature with tone feature to distinguish the change of the building from the change of other ground objects, and thus detection accuracy of the building is increased and the false detection rate is reduced.

Description

Technical field [0001] The invention relates to a building change detection method, in particular to a multispectral image building change detection method. Background technique [0002] Traditional remote sensing image change detection methods are based on the analysis of spectral information based on the pixel level, and their common feature is that they can only use the intensity of the image, that is, the statistical information of the gray value. The change detection performance is severely restricted by the following factors: image radiation difference, registration error and threshold selection, and the type of feature change detected by pixel-level changes cannot be determined, and all features are obtained. [0003] High-resolution remote sensing images have brought major changes to the development of remote sensing technology. In high-spatial resolution satellite images, the structure, texture and details of the ground feature landscape are very clearly expressed, except ...

AI Technical Summary

Problems solved by technology

The use of object-oriented classification is mainly manual participation, and the process is cumbersome.

[0010] Wang Min et al. proposed an image change detection method based on multi-feature evidence fusion. By calculating the structural similarity of the texture, gradient, and edge of the two-temporal image, the D-S evidence theory was constructed and the evidence was synthesized. Areas of change, but rules are harder to pin down

[0011] Current research shows that no single change detection method has an absolute advantage

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