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High-resolution remote sensing image building automatic extraction method and system by using shadow

An automatic extraction, high-resolution technology, used in instruments, character and pattern recognition, computer parts, etc., can solve problems such as inseparability and reduced automation

Active Publication Date: 2016-04-27
YANGTZE UNIVERSITY
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Problems solved by technology

This type of method does not require prior knowledge, but the commonly used supervised classification must rely on sample training, and sample selection is often inseparable from manual assistance, resulting in a reduced degree of automation

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  • High-resolution remote sensing image building automatic extraction method and system by using shadow
  • High-resolution remote sensing image building automatic extraction method and system by using shadow
  • High-resolution remote sensing image building automatic extraction method and system by using shadow

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Embodiment Construction

[0078] In order to facilitate those of ordinary skill in the art to understand and implement the present invention, the present invention will be described in further detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the implementation examples described here are only used to illustrate and explain the present invention, and are not intended to limit this invention.

[0079] In view of the demand for universality and intelligence of building extraction methods in related remote sensing applications, as well as the low degree of automation of building extraction methods, the universality caused by over-reliance on data sources, prior knowledge, artificial assistance, etc. According to the characteristics of building shadows closely adjacent to buildings, it can be achieved by designing a high-resolution optical image based on fully utilizing the shadow characteristics of buildings for the design of automatic classification a...

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Abstract

The invention discloses a high-resolution remote sensing image building automatic extraction method and system by using shadow. The method comprises the steps of: firstly performing sample automatic extraction of shadow, vegetation, bare land, and building on an image, combining an SVM classification principle and realizing automatic classification, and extracting a building initial result; and then performing post-processing optimization on the initial result, the post-processing optimization including morphology pre-processing, missed detection supplement and building verification or the like, and outputting the building final result. The system includes a sample area automatic extraction module, an SVM classifier training and outputting module, and a post-processing optimization module. The building extraction automation degree is effectively improved and the precision can be ensured by designing the sample automatic extraction method and effective post-processing optimization measures.

Description

technical field [0001] The invention belongs to the technical field of remote sensing image applications, in particular to a method and system for automatically extracting buildings from high-resolution remote sensing images using shadows. Background technique [0002] Buildings are important ground objects, and the automatic extraction technology of buildings is an important aspect of remote sensing interpretation research. Many remote sensing applications, such as continuous update of urban planning and map drawing, rapid emergency response, infrastructure construction, disaster planning and management, etc. Both need to quickly extract building information, but the current building extraction is too dependent on manual work, and the degree of automation is low. [0003] Current building extraction methods are often designed according to application requirements and available data. Optical imagery, LiDAR data, and SAR data are common data sources. Based on LiDAR, SAR, an...

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Application Information

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IPC IPC(8): G06K9/00G06K9/62
CPCG06V20/176G06V20/188G06V2201/07G06F18/2411
Inventor 高贤君杨元维
Owner YANGTZE UNIVERSITY
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