Change Detection Method of Remote Sensing Image

Abstract

The invention discloses a remote sensing image change detection method. The detection method comprises the implementation steps that (1) remote sensing images before and after changes are input; (2) whether the input images are color images or not is judged; (3) a dark primary color channel image is constructed; (4) whether fog exists on the color remote sensing images or not is judged; (5) the color remote sensing images with the fog are defogged; (6) the images are segmented; (7) classification and recognition are performed; (8) change detection is performed. According to the remote sensing image change detection method, the remote sensing images affected by fog and haze can be well processed, and meanwhile different types of ground object change detection images can be respectively obtained. The method has a wide application range and high detection accuracy and can be applied to the technical fields of ground object change monitoring before and after earthquakes and dynamic monitoring of crop growth states.

Description

technical field [0001] The invention belongs to the technical field of image processing, and further relates to a remote sensing image change detection method in the technical field of image segmentation and image classification and recognition. This method can quickly detect the change information of two-temporal remote sensing images, and can be applied to the monitoring of changes in ground features before and after earthquakes, and the dynamic monitoring of crop growth status. Background technique [0002] Change detection is to detect the change information of the ground objects in the area over time by analyzing multiple remote sensing images in the same area at different times. With the development of remote sensing technology and information technology, multi-temporal remote sensing image change detection has become an important direction of current remote sensing image analysis research. [0003] In the research of multi-temporal remote sensing image change detecti...

AI Technical Summary

Problems solved by technology

Although this method can solve the problem of low detection accuracy and narrow application range of a single type of difference map, it still has the disadvantage that the method operates on pixels, thus ignoring the change results for a specific object, and only obtains Two types of results, changed and unchanged, cannot classify remote sensing images, and cannot obtain change detection images of different ground objects

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