Remote-sensing image road network extraction technology based on combined filtering

A remote sensing image and joint filtering technology, applied in the field of remote sensing applications, can solve problems such as retaining road features and achieve the effect of road structure enhancement

Active Publication Date: 2017-01-04
国交空间信息技术(北京)有限公司
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

For such methods, it is difficult to preserve road features while

Method used

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  • Remote-sensing image road network extraction technology based on combined filtering
  • Remote-sensing image road network extraction technology based on combined filtering
  • Remote-sensing image road network extraction technology based on combined filtering

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Experimental program
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Embodiment

[0057] In cognitive psychology, the laws of human visual cognition can be judged and supported from the following information:

[0058] Anisotropy, the intensity variation of the visually significant structure in the image will form the main direction, which does not change equally in each direction;

[0059] Aperiodic, the texture details in local areas will appear different periodically, and human beings' cognition of periodic texture details is easily suppressed and more attention is paid to the details of aperiodic appearance;

[0060] Local directionality. In a local area, the intensity changes of prominent visual structures usually have a consistent directionality, while some texture detail information does not have such properties.

[0061] like figure 1 Shown is flow chart of the present invention, mainly comprises following three steps:

[0062] S1. Input the source image, and calculate the road salient structure metric model M of the source image p , the saliency ...

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Abstract

The present invention discloses a remote-sensing image road network extraction technology based on the combined filtering. A complete road substantial structure mathematic measurement model is built through combination of the human vision cognitive rules according to the aperiodicity, the anisotropy and the local directivity of the substantial image structure formed in the human cognition; under the guidance of the road substantial structure mathematic measurement model, a self-adaptive smooth filtering function is built through combination of the steam line directivity, and the self-adaptive smoothness of the road remote sensing image is realized through combination of the pixel point space distance Gauss function; and under the guidance of the road substantial structure measurement model, a self-adaptive impact filtering function is defined through combination of the maximin value filtering, and the impact enhance intensities of the function generated in different areas are different so as to realize the self-adaptive impact filtering enhancement, retain the substantial road structure while smoothing the non-road structure area and realize the preprocessing of the remote sensing image in the road extraction process.

Description

technical field [0001] The invention relates to the field of remote sensing applications, in particular to a joint filtering-based remote sensing image road network extraction technology. Background technique [0002] Remote sensing technology has the characteristics of high efficiency, real-time and information diversification. As an advanced method of earth observation, it has played an important role in the field of urban transportation. [0003] In the road extraction based on remote sensing technology, traditional road extraction algorithms mainly rely on the geometric and geographical features of the road, and use the identification rules of the road area to extract the road. In recent years, the field of road extraction tends to build complex systems for extracting road information, and many methods use correlation filtering techniques. Traditional road extraction filtering methods, such as Gaussian filtering and median filtering, all perform consistent filtering on ...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/36G06K9/44
CPCG06V20/182G06V10/20G06V10/34
Inventor 臧彧王程杨文韬罗伦李迪龙
Owner 国交空间信息技术(北京)有限公司
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