A Multispectral Image Classification Method Based on Surface Wave CNN

A multi-spectral image and classification method technology, applied in the field of multi-spectral image classification based on surface wave CNN, can solve the problem of multi-spectral image multi-scale, multi-direction, multi-resolution characteristics, multi-spectral image is difficult to get higher classification Accuracy and other issues to achieve the effect of improving classification accuracy

Active Publication Date: 2020-09-29
XIDIAN UNIV
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AI Technical Summary

Problems solved by technology

[0007] Since these feature extraction methods do not take into account the multi-scale, multi-directional, and multi-resolution characteristics of multispectral images, it is difficult to obtain high classification accuracy for multispectral images with complex backgrounds.

Method used

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  • A Multispectral Image Classification Method Based on Surface Wave CNN
  • A Multispectral Image Classification Method Based on Surface Wave CNN
  • A Multispectral Image Classification Method Based on Surface Wave CNN

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Experimental program
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Embodiment

[0070] 1. Simulation conditions:

[0071] The hardware platform is: Intel(R) Xeon(R) CPU E5650@2.13GHz

[0072] Graphics card: Quadro K2200 / PCIe / SSE2, 2.40GHz

[0073] Memory: 8G

[0074] The software platform is: Caffe.

[0075] 2. Simulation content and results:

[0076] Carry out experiments under the above-mentioned simulation conditions with the method of the present invention, namely randomly select 5% of marked pixels as training samples from each category of multispectral data respectively, and use the whole picture as test data to obtain the following: image 3 classification results.

[0077] From image 3 It can be seen that the regional consistency of the classification results is good, and the edges of different regions are also very clear after division, and the detailed information is maintained.

[0078] Then reduce the training samples successively, so that the training samples account for 4%, 3%, and 2% of the total number of samples, and compare the cl...

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Abstract

The invention discloses a method for classifying multispectral images based on surface wave CNN. The multispectral images to be classified are input, the multispectral data are normalized to obtain a matrix, and the normalized matrix is ​​obtained by taking the center pixel. block to obtain the training data set and test set; construct a classification model based on surface wave CNN; use the training data set to train the classification model; use the trained classification model to classify the test data set. The invention introduces a multi-scale depth filter, improves the classification accuracy of multi-spectral images, and can be used for object classification.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a multispectral image classification method based on surface wave CNN. Background technique [0002] Multispectral remote sensing is a remote sensing technology that uses sensors with more than two spectral channels to simultaneously image ground objects. It divides the electromagnetic wave information reflected by objects into several spectral segments for reception and recording. Multi-spectral remote sensing can not only distinguish ground objects according to the difference in image shape and structure, but also distinguish ground objects according to the difference in spectral characteristics, which expands the amount of remote sensing information. Both the multi-spectral photography used in aerial photography and the multi-spectral scanning used in land satellites can obtain remote sensing data of different spectral bands, and the images or data of sub-...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/62G06N3/04
CPCG06N3/045G06F18/24G06F18/214
Inventor 焦李成张文华马文萍杨淑媛侯彪刘芳尚荣华张向荣马晶晶张丹唐旭
Owner XIDIAN UNIV
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