Remote sensing image change detection method and device

Abstract

The embodiment of the invention provides a remote sensing image change detection method and device, and the method comprises the steps of carrying out the geometric registration of an obtained remotesensing image of a front time phase and an obtained remote sensing image of a rear time phase; carrying out multi-scale segmentation on the remote sensing image of the front time phase to obtain a segmented vector diagram, and nesting the vector diagram on the geometrically registered remote sensing image of the front time phase and the geometrically registered remote sensing image of the rear time phase to obtain a to-be-detected pattern spot pair of the front time phase and the rear time phase; utilizing an automatic change detection algorithm to carry out automatic change detection on the pattern spot pairs of the front and rear time phases to be detected, and determining a non-change pattern spot set and a possible change pattern spot set according to a detection result; and clusteringthe possible change pattern spot set, and applying the clustered possible change pattern spot set to manual judgment to determine a change pattern spot. According to the technical scheme, the efficiency of manually extracting change information in surveying and mapping production can be improved.

Description

technical field [0001] The invention relates to the field of image processing, in particular to a remote sensing image change detection method and device. Background technique [0002] With the development of earth observation technology and the continuous improvement of the resolution of remote sensing images, extracting ground object information from remote sensing images has become a very important direction. Land resource management and planning, environmental protection, surveying and mapping geographic information, etc. all require rapid and accurate monitoring of these land cover changes. There are mainly two types of extraction methods for change detection of remote sensing images: 1) Completely manual extraction. Experienced change monitoring operators superimpose the front and rear remote sensing images of the two scenes, and use tools such as rolling shutters to judge the images line by line. Tuban carefully checked. Under normal circumstances, it has the highes...

AI Technical Summary

Problems solved by technology

However, once a missed detection occurs, it is necessary to manually check the images of the remaining 95% of the patches from scratch

Therefore, for the automatic change detection algorithm, once the missed detection rate does not meet the requirements, the result will be difficult to meet the requirements of surveying and mapping production, and manual inspection is required

From this perspective, the results of automated extraction cannot improve any operational efficiency

[0003] Therefore, due to the particularity of the change detection business, when most other surveying and mapping products (DOM, DEM, DSM, etc.) Visual interpretation and extraction, existing computer automatic algorithms and tools cannot meet the high-precision change detection requirements for surveying and mapping production

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