Remote sensing image road segmentation method based on context information and attention mechanism

A technology of remote sensing images and attention, which is applied to computer components, character and pattern recognition, instruments, etc., can solve the problems of spatial information loss, image resolution reduction, and failure to consider geometric topological structures, etc., to avoid loss of positional information , avoid explosion and disappearance, and ensure the effect of splitting effect

Inactive Publication Date: 2021-01-05
TAIYUAN UNIV OF TECH
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Problems solved by technology

These methods do not take into account the geometric topology of the road as a whole, and lack of full use of context information; at the same time, the ima...

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  • Remote sensing image road segmentation method based on context information and attention mechanism
  • Remote sensing image road segmentation method based on context information and attention mechanism
  • Remote sensing image road segmentation method based on context information and attention mechanism

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Embodiment Construction

[0052]Such asFigure 1 to Figure 6 As shown, a remote sensing image road segmentation method based on context information and attention mechanism of the present invention includes the following steps:

[0053]Step 1: Divide the remote sensing image data set into a training set and a test set according to a certain ratio. The remote sensing image data set is obtained by a remote sensing satellite, and the remote sensing image data set includes the original image and manually labeled labeled data images; The remote sensing image data of the training set is preprocessed to obtain the remote sensing image after data enhancement;

[0054]Step 2: Build a remote sensing image road segmentation network: The remote sensing image road segmentation network includes a context information extraction module and an attention module. The building steps include:

[0055]Step 2.1: Using the U-Net network model as the basic network, replace the encoder module in the U-Net network model with the Resnet-34 networ...

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Abstract

The invention discloses a remote sensing image road segmentation method based on context information and an attention mechanism, and belongs to the technical field of remote sensing image road segmentation methods. The technical problem to be solved is to provide an improvement of a remote sensing image road segmentation method based on context information and an attention mechanism. According tothe technical scheme, the method comprises the steps of dividing a remote sensing image data set into a training set and a test set according to a certain proportion; establishing a remote sensing image road segmentation network, wherein the remote sensing image road segmentation network comprises a context information extraction module and an attention module; inputting the preprocessed trainingset data into a remote sensing image road segmentation network, and training the remote sensing image road segmentation network; inputting the test set data into a trained remote sensing image road segmentation network, and outputting an accurate segmentation result of the image road data; the method is applied to image road segmentation.

Description

Technical field[0001]The present invention is a remote sensing image road segmentation method based on context information and attention mechanism, belonging to the technical field of remote sensing image road segmentation methods.Background technique[0002]In recent years, with the continuous increase and improvement of the number and technology of remote sensing satellites launched in the world, the resolution of remote sensing satellite images has also been greatly improved. Therefore, high-resolution remote sensing images have become an important data source for digital image processing. At the same time, high-resolution satellite remote sensing images can provide a wealth of feature information, with fast update speed and high accuracy. Road extraction from remote sensing images has played an important role in urban planning, traffic management, vehicle navigation, map update and other fields, and has become a research hotspot in recent years.[0003]However, because remote sensin...

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Application Information

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IPC IPC(8): G06K9/00G06K9/34G06K9/62G06N3/04
CPCG06V20/13G06V10/267G06N3/045G06F18/214G06F18/253
Inventor 陈泽华杨佳林郭学俊刘晓峰赵哲峰李龙
Owner TAIYUAN UNIV OF TECH
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