SVM-based recognition method of building angular points in high-resolution optical image

A high-resolution, optical image technology, applied in character and pattern recognition, instruments, computer components, etc., can solve problems such as gaps, achieve the effect of improving accuracy and generalization ability

Active Publication Date: 2017-03-22
GUILIN UNIVERSITY OF TECHNOLOGY
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Problems solved by technology

[0003] Remote sensing technology is becoming more and more mature, and its application fields are constantly expanding. However, the computer interpretation and interpretation technology of high-resolution remote sensing images still has a large gap with the needs of practical applications.

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  • SVM-based recognition method of building angular points in high-resolution optical image
  • SVM-based recognition method of building angular points in high-resolution optical image
  • SVM-based recognition method of building angular points in high-resolution optical image

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Embodiment

[0027] (1) Perform orthorectification processing on the obtained high-resolution remote sensing images and corresponding DEM images through ENVI and Erdas remote sensing image digital processing software to obtain corrected high-resolution remote sensing images containing elevation information.

[0028] (2) Since plant leaves have strong absorption properties in the visible red band and strong reflection properties in the near-infrared band, according to this feature, the vegetation water body is separated from the image first to improve the classification accuracy. Therefore, the vegetation in the high-resolution remote sensing image is separated from the image by NDVI (Normalized Difference Vegetation Index) to improve the classification accuracy of the following step (3). Among them, NIR is the reflection value of the near-infrared band, and R is the reflection value of the red band.

[0029] NDVI=(NIR-R) / (NIR+R) (-1<=NDVI<=1) (1)

[0030] A negative value of NDVI means th...

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Abstract

The invention discloses an SVM-based recognition method of building angular points in a high-resolution optical image. The process of the method comprises the steps that the high-resolution optical image is subjected to ortho-rectification, the influences of vegetation on a classification result are removed through an NDVI, a binary support vector machine (SVM) is used for marking out building blocks in the image in a classified mode, a candy operator is used for performing edge detection on the area where the building blocks are located, a structure chart of point sets of building nodes is obtained through hough transformation, and the SVM is used for classifying the point sets to obtain the building angular points. Through the method, the recognition precision of the building angular points in the optical image can be greatly improved, and the information extraction rate of buildings and other artificial objects in the image with a high spatial resolution is increased.

Description

technical field [0001] The invention relates to the field of high resolution remote sensing image recognition, in particular to a method for recognition and extraction of building corners in high spatial resolution optical images. Background technique [0002] The extraction and shape mapping of buildings in high-resolution remote sensing images are key factors in the construction of future smart cities, and in the process of building extraction, building corner recognition is an important part. In recent years, the spatial resolution of satellite remote sensing images has reached the sub-meter level, and the support vector machine developed from statistical theory has also achieved good promotion and application in the field of pattern recognition and classification. The rapid development of computer algorithm technology provides a new research method for the recognition of building corners. [0003] Remote sensing technology is becoming more and more mature, and its appli...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06K9/00G06K9/46
CPCG06V20/176G06V10/44G06F18/2411
Inventor 李百寿李灵芝张强
Owner GUILIN UNIVERSITY OF TECHNOLOGY
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