Multispectral image classification method based on dual-channel DCGAN and feature fusion

A multi-spectral image and feature fusion technology, which is applied in the field of multi-spectral image classification and image processing, can solve the problems of cumbersome calculation process, different spectra of the same object and the same spectrum of different objects, and complexity, so as to overcome the lack of feature information and rich feature information , the effect of improving the classification accuracy

Active Publication Date: 2018-04-20
XIDIAN UNIV
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Problems solved by technology

However, the shortcomings of this method are that the feature extraction design of this method relies on human experience, which is complex and time-consuming, and the combination of features is usually not suitable for scenes where the pixel contrast is not obvious.
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  • Multispectral image classification method based on dual-channel DCGAN and feature fusion
  • Multispectral image classification method based on dual-channel DCGAN and feature fusion
  • Multispectral image classification method based on dual-channel DCGAN and feature fusion

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[0038] The present invention will be further described below with reference to the accompanying drawings.

[0039] Refer to the attached figure 1 , the steps of the implementation of the present invention are described in detail as follows.

[0040] Step 1, input the multispectral image.

[0041] Input multispectral images of five regions imaged by two different satellites, one is Sentinel-2 satellite, the other is landsat-8 satellite, the five regions are berlin, hong_kong, paris, rome, SaoPaulo, each The region contains two multispectral images, the first multispectral image contains 10-band images and the second multi-spectral image contains 9-band images.

[0042] Step 2, normalize the image of each band of each multispectral image.

[0043] The steps of the normalization process are as follows:

[0044] Step 1: Divide each pixel value in the image of each band in the first multispectral image by the pixel maximum value of the band image to obtain the normalized pixel ...

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Abstract

The invention discloses a multispectral image classification method based on dual-channel deep convolutional generative adversarial network (DCGAN) and feature fusion. The method comprises steps of: inputting multispectral images; normalizing the image of each band of each multispectral image; obtaining a multispectral image matrix; obtaining a data set; creating a dual-channel DCGAN model; training a dual-channel DCGAN classification model; and classifying a test data set. The multispectral image classification method introduces the dual-channel DCGAN, combines the feature fusion, extracts avariety of multispectral high-level feature information in multiple directions, enhances the feature characterization ability, and improves the classification effect.

Description

technical field [0001] The invention belongs to the technical field of image processing, and further relates to a multispectral image classification method based on a dual-channel generative confrontation network DCGAN (Deep Convolutional Generative Adversarial Networks) and feature fusion in the technical field of multispectral image classification. The invention can be used to classify ground objects including water areas, fields, cities and the like in multispectral images. Background technique [0002] Multispectral image is a kind of remote sensing image, which is obtained by repeatedly shooting the same target in multiple bands. The application value of multi-spectral images is more and more extensive, such as in the fields of aviation and aerospace ground detection, land surveying and mapping, disaster detection and so on. Image classification is an important direction in the research content of multispectral images. There are many traditional classification methods...

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Application Information

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IPC IPC(8): G06K9/62G06K9/66G06N3/04
CPCG06V30/194G06N3/045G06F18/2413
Inventor 焦李成屈嵘汶茂宁马文萍杨淑媛侯彪刘芳陈璞花古晶张丹唐旭马晶晶
Owner XIDIAN UNIV
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