Remote sensing image classification method based on capsule network

A remote sensing image and classification method technology, applied in the field of remote sensing image processing, can solve the problems of inability to effectively capture remote sensing images, inability to effectively extract advanced features, poor classification effect, etc., and achieve good classification effect, simple structure, and easy to reproduce effect

Pending Publication Date: 2020-08-28
YUNNAN POWER GRID CO LTD ELECTRIC POWER RES INST
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Problems solved by technology

[0005] The invention provides a remote sensing image classification method based on a capsule network to solve the problems existing in the prior art that the hierarchica

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  • Remote sensing image classification method based on capsule network
  • Remote sensing image classification method based on capsule network
  • Remote sensing image classification method based on capsule network

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[0099] Example

[0100] In this embodiment, the above-mentioned classification method is described by using a remote sensing image with 256*256 pixels.

[0101] like figure 2As shown, obtain the original remote sensing image, each original remote sensing image has a corresponding category label; by cutting the main area of ​​the original remote sensing image and adjusting the image size, the remote sensing image with the pixel of 256*256 is obtained as the sample set; the The image sample set with a pixel of 256*256 is divided into training set and test set; a VGG16-capsule network model is built, and each remote sensing image in the divided training set is input into the VGG16-capsule network model for learning; the loss function formula is used to calculate The loss value between the output value of the VGG16-capsule network model (ie the predicted value) and the actual class label (ie the true value) of each remote sensing image in the training set, adjust the VGG16-capsu...

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Abstract

The invention provides a remote sensing image classification method based on a capsule network. The remote sensing image classification method comprises the following steps: inputting an original remote sensing image; processing the original remote sensing image into a sample set with consistent pixels; dividing a training set and a test set from the sample set; building a VGG16-capsule network model; training the VGG16-capsule network model; and utilizing the trained VGG16-capsule network model to classify the test set. According to the method, the hybrid network model of the VGG16 network model and the capsule network is adopted, the hierarchical structure of the remote sensing image can be effectively captured, and appropriate advanced features are extracted, so that the remote sensingimage is classified, and the classification effect is better.

Description

technical field [0001] The invention relates to the technical field of remote sensing image processing, in particular to a remote sensing image classification method based on a capsule network. Background technique [0002] With the development of remote sensing technology, existing technologies can easily obtain various types of high-resolution remote sensing images, such as multi / hyperspectral and synthetic aperture radar. From remote sensing images, urban environment, traffic, hydrology, Therefore, it is particularly important to effectively understand the content of remote sensing images, and the requirements for intelligent recognition and classification methods of remote sensing images are getting higher and higher. In recent years, deep learning methods have been widely used in the field of image processing, and deep learning methods have also achieved remarkable results in image processing in the fields of medicine, hydrology, and urban environment. [0003] In the ...

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Application Information

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IPC IPC(8): G06K9/62G06K9/00G06N3/04G06N3/08
CPCG06N3/084G06V20/13G06N3/045G06F18/24G06F18/214
Inventor 黄修乾王家豪马仪周仿荣马御棠黄然文刚
Owner YUNNAN POWER GRID CO LTD ELECTRIC POWER RES INST
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