High-resolution remote sensing building extraction method combining semantic segmentation and edge detection

A semantic segmentation and high-resolution technology, applied in the field of high-resolution remote sensing building extraction, can solve the problems of non-closed, edge discontinuity, etc., and achieve the effect of improving accuracy, good restoration results, and wide applicability

CN113689445APending Publication Date: 2021-11-23ZHEJIANG UNIV OF TECH
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Publication Date
2021-11-23

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Abstract

The invention discloses a high-resolution remote sensing building extraction method combining semantic segmentation and edge detection, and belongs to the technical field of remote sensing image target extraction. The method comprises: firstly, by adopting a semantic segmentation network and a deep edge detection network, predicting a building roof surface and an edge graph respectively; then, denoising and skeleton extraction are carried out on the building edge graph; on the basis, in combination with a building roof surface prediction map, carrying out deburring and broken line repairing processing on the building edge map; and finally, vectorizing the building edge graph to obtain a building roof contour extraction result. According to the method, the problem that the building edge in the deep convolutional neural network model prediction map is discontinuous and not closed can be solved, the extraction precision of the building edge of the high-resolution remote sensing image is improved, and the method is good in performance and wide in applicability in extraction of roof forms of different types of buildings.
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Description

technical field

[0001] The invention belongs to the technical field of remote sensing image target extraction, and in particular relates to a high-resolution remote sensing building extraction method. Background technique

[0002] Building extraction based on remote sensing images provides important data support for urban and rural planning, dynamic monitoring, disaster assessment, land use analysis, map update, etc. With the continuous development of remote sensing technology, the spatial resolution of remote sensing images that people can obtain is getting higher and higher. Buildings present richer spatial and geometric features on high-spatial-resolution remote sensing images (hereinafter referred to as high-resolution remote sensing images), and the details inside the roof of buildings are also clearly visible, which brings opportunities for building extraction tasks with challenges.

[0003] Traditional building extraction methods usually require manual construction ...

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Embodiment Construction

[0061] Below through embodiment, further illustrate the present invention in conjunction with accompanying drawing.

[0062] The technical solution of the present invention is a high-resolution remote sensing building extraction method combining semantic segmentation and edge detection, comprising the following steps:

[0063] Step 1. Build a building sample library: According to the geographical location of the research area, obtain high-resolution remote sensing images covering the entire research area; use artificial visual interpretation to mark the roofs of buildings on the high-resolution remote sensing images in the research area, Get building face labels and line labels. Crop the high-resolution remote sensing image and the corresponding label map in the research area, and the size is h×w. In the embodiment of the present invention, non-overlapping cropping is adopted, and the size of the cropped image and label is 512×512, thereby constructing the building Sample lib...