Method of extracting rectangular building from remote sensing image

Abstract

The invention relates to the field of image processing, and discloses a method of extracting a rectangular building from a remote sensing image. The method comprises the steps of obtaining a plurality of superpixel region blocks by superpixel segmentation of a remote sensing image; determining two seed points on a target building in the remote sensing image; merging the plurality of superpixel region blocks based on the determined seed points; carrying out corner detection for the remote sensing image; calculating to generate a corner distance saliency map related to each pixel point in the remote sensing image based on the corner detection result; carrying out binary segmentation for the corner distance saliency map; determining priori information based on the merging result of the plurality of superpixel region blocks and the distance saliency map after binary segmentation; obtaining a building segmentation result by segmenting the remote sensing image based on the priori information; carrying out morphological image processing for the building segmentation result; and obtaining a rectangular target building by rectangular fitting of the building segmentation result after the morphological image processing. The above the method can accurately extract the rectangular building from the remote sensing image.

Description

technical field [0001] The invention relates to the field of image processing, in particular to a method for extracting rectangular buildings from remote sensing images. Background technique [0002] Artificial ground objects are an important content of high-resolution remote sensing images, and buildings, as the most important artificial ground objects, are closely related to people's lives. Therefore, the extraction of artificial ground objects such as buildings in high-resolution remote sensing images has always been is the focus of the research. The characteristics of buildings in high-resolution remote sensing images are as follows: in complex scenes and areas with dense buildings, it is quite difficult to locate buildings; more buildings have the same object and different spectra, and there are foreign objects in buildings and other objects The phenomenon of the same spectrum; the shapes of buildings are diverse, and the automatic extraction and shape fitting of build...

AI Technical Summary

Problems solved by technology

The texture of the building is also a significant identification feature. Through the analysis of the texture, the corresponding building target can be extracted. The texture-based feature-based extraction method is more effective for processing low-resolution images. Targets in high-resolution remote sensing images Rich details lead to complex texture features, and there are phenomena such as "same spectrum and foreign objects", which makes it difficult to separate the texture features of buildings from other target texture features, reducing the extraction accuracy

[0007] Although the above algorithm solves the problem of building extraction to a certain extent, there are still problems of complex extraction process and low extraction accuracy.

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