Method for extracting linear ground objects

Abstract

The invention provides a method for extracting linear ground objects. A remote-sensing image is preprocessed and a preprocessed image is obtained; a vegetation region is extracted from the preprocessed image and removed, and a target region is obtained; features of the image of the target region are extracted according to the types of the linear ground objects and vectorized, and a linear ground object vectorization file is obtained. According to the method, first, the remote-sensing image is preprocessed and the vegetation region is extracted to remove other ground objects around the linear ground objects, and thus the target region can be highlighted in the image. Then, features of the target region are extracted through dual threshold filtering according to the different types of linear ground objects. The method for extracting the linear ground objects can solve the problem that when single threshold filtering extraction is performed, an appropriate threshold needs to be selected, has good ability to detect the edges of the linear ground objects, avoids the spiced salt phenomenon furthest, facilitates vectorization and compensates for the defect that in the prior art, the linear ground objects can only be detected and extracted qualitatively to elevate the quality level of land.

Description

technical field [0001] The invention relates to the technical field of remote sensing image processing, in particular to a method for extracting linear ground objects. Background technique [0002] With the rapid development of high-altitude remote sensing impact technology, high-altitude remote sensing image data and the analysis and processing of remote sensing image data are widely used in land and resource survey and monitoring, basic geographic data update, etc. Among them, the linear infrastructure of cultivated land such as irrigation and drainage ditches and field roads in the obtained bottom surface remote sensing images is one of the important factors affecting farmland identification. The quality evaluation of farmland identification has value and significance. [0003] The traditional method is to manually interpret images based on remote sensing data, but the error is large, and the efficiency is too low, which requires a lot of manual labor. In addition, in t...

AI Technical Summary

Problems solved by technology

[0003] The traditional method is to manually interpret images based on remote sensing data, but the error is large and the efficiency is too low, which requires a lot of manual labor

In addition, in the process of processing remote sensing image data, vegetation and other features around linear features will interfere with the linear features that need to be extracted. Extraction poses greater difficulties

It can only extract the ground features qualitatively, and cannot meet the requirements of rapid assessment of the quality level of cultivated land in land consolidation areas

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