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A multispectral image classification method based on a double-channel multi-feature fusion network

A multi-feature fusion and multi-spectral image technology, applied in the field of multi-spectral image classification, can solve the problems of single spectral information and redundant information of single-satellite single-spectral segment, improve classification accuracy, ensure integrity and discrimination, improve The effect of testing accuracy

Inactive Publication Date: 2017-12-12
XIDIAN UNIV
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Problems solved by technology

[0005] The purpose of the present invention is to overcome the above-mentioned deficiencies and provide a multi-spectral image classification method based on a dual-channel multi-feature fusion network to solve the problem of single-satellite single-band spectral information and the problem of information redundancy after fusion in existing methods

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  • A multispectral image classification method based on a double-channel multi-feature fusion network
  • A multispectral image classification method based on a double-channel multi-feature fusion network
  • A multispectral image classification method based on a double-channel multi-feature fusion network

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Embodiment Construction

[0037] The present invention will be further described below in conjunction with the accompanying drawings.

[0038] see figure 1 , the specific implementation steps of the present invention are as follows:

[0039]Step 1, superimpose and fuse the 9 bands taken by the landsat_8 satellite to obtain the fused multispectral feature L, where L=(L 1 , L 2 ,...,L i ), L i Indicates the multispectral feature of the i-th band of landsat_8, i=9 means that there are 9 bands in total, and the dimension of L is M×N×i, L i The dimension of is M×N, where M represents the height of the spectral feature matrix, and N represents the width of the spectral feature matrix.

[0040] Step 2, superimpose and fuse the 10 bands taken by the sentinel_2 satellite to obtain the fused multispectral feature L', where L'=(L 1 ', L' 2 ,...,L′ j ), L' j Represents the multispectral feature of the jth band of the sentinel_2 satellite, j=10 means that there are 10 bands in total, and the dimension of L...

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Abstract

The invention provides a multispectral image classification method based on a double-channel multi-feature fusion network. The method comprises the steps of: fusing multispectral features of different wave bands of two satellites to obtain features L and L'; performing normalization processing on the L and the L' to obtain Lnorm and L' norm; selecting pixel blocks randomly on the Lnorm and the L' norm to form a training set and a validation set and form feature matrixes Wtrain and Wval based on image blocks and obtaining a feature matrix Wtest of a testing set according to a feature matrix of sao-paulo city; building a classification model of a double-channel all-convolutional neural network; training the classification model by using the feature matrix Wtrain of the training data set and the feature matrix Wval of the validation data set; classifying the feature matrix Wtest of the test data set by using the trained classification model. According to the invention, the double-channel all-convolutional neural network is used for multispectral image classification; compared with a common all-convolutional neural network, the double-channel all-convolutional neural network can increase the classification accuracy.

Description

technical field [0001] The invention belongs to the field of image processing, and in particular relates to a multi-spectral image classification method based on a dual-channel multi-feature fusion network. Background technique [0002] As a kind of remote sensing image, multispectral image has its own characteristics. On the one hand, it is to make full use of various electromagnetic spectrum segments that can pass through the atmosphere, and to expand to infrared, far-infrared, and microwaves; on the other hand, it is to subdivide the spectral segments. Generally, typical ground objects have their spectral waveform characteristics. Due to the narrow band width, large number and continuity, high-dimensional multispectral images can provide approximately continuous spectral information of ground objects with high spectral resolution. [0003] There are three levels of image fusion, data-level fusion, feature-level fusion and decision-level fusion. The current multispectral...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06N3/04G06N3/08
CPCG06N3/084G06V10/58G06N3/045G06F18/2148G06F18/253
Inventor 焦李成屈嵘高丽丽马文萍杨淑媛侯彪刘芳尚荣华张向荣张丹唐旭马晶晶
Owner XIDIAN UNIV
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