Method for detecting changes in surrounding environment of water body based on forward and backward heterogeneity of remote sensing images

Abstract

The invention relates to a method for detecting changes in the surrounding environment of a water body based on the forward and backward heterogeneity of remote sensing images. According to the invention, an SLIC (Simple Linear Iterative Cluster) multi-scale segmentation result of superimposed images is relatively uniform, nearly square ground feature objects can be obtained in regions such as water bodies and vegetation with uniform ground feature distribution, boundary information of ground features in the images are not damaged when regions with complicated ground feature distribution are processed, and the ground feature objects are not be too fragmented, thereby being more in line with true ground feature distribution. In addition, problems are detected through analyzing changes in the surrounding environment of the water body, and a hybrid feature space is built by organically combining spectrum, texture and index features. The method has good effects on processing of pseudo-change information, which shows that the method has good detection effects for pseudo-change information such as water quality changes and vegetation phenological changes.

Description

technical field [0001] The invention relates to a method for detecting changes in the surrounding environment of a water body based on the forward and reverse heterogeneity of remote sensing images, and belongs to the technical field of remote sensing image detection. Background technique [0002] Remote sensing image change detection involves relevant knowledge of multiple disciplines such as geography, information science, and computer science, and is currently a hot research direction in remote sensing image analysis. Remote sensing image change detection refers to the use of image processing, statistical analysis and other technologies to compare remote sensing image data in the same geographical area but different time phases, and point out the location area where the type of ground features changes by analyzing the change information contained in the multi-temporal images. [0003] At present, the research on the change detection technology of remote sensing images mai...

AI Technical Summary

Problems solved by technology

High-resolution remote sensing images can provide a wealth of detailed information on ground features, but the distribution of ground features in the surrounding environment of water bodies is complex, and the phenomenon of "same object with different spectrum" and "same spectrum with different objects" is serious, resulting in a lot of interference information

At the same time, due to seasonal water level fluctuations, water quality changes, and vegetation phenological changes, there are many "pseudo-change information" in multi-temporal images, and the detection of changes in the surrounding environment of water bodies faces new challenges.

There are still many difficulties and problems to be overcome and solved in the existing remote sensing image change detection methods. How to effectively use the rich ground feature details in remote sensing images to distinguish the interesting ground feature change information from the uninteresting interference information, "pseudo Change information" to form relatively accurate and robust change detection results is an important research content of change detection today.

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