Spatial spectrum attention hyperspectral image classification method based on Octave convolution

A technology of hyperspectral image and classification method, which is applied in the field of spatial spectral attention hyperspectral image classification based on Octave convolution, can solve the problems of disappearing network training gradient, poor robustness, and large distance between the same categories, and achieves hyperspectral image classification. The information contained in the features is comprehensive and detailed, the classification accuracy is improved, and the feature representation is enhanced.
CN110516596AActive Publication Date: 2019-11-29XIDIAN UNIV
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Patent Information

Authority / Receiving Office
CN Β· China
Patent Type
Applications(China)
Current Assignee / Owner
XIDIAN UNIV
Publication Date
2019-11-29

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Abstract

The invention discloses a spatial spectrum attention hyperspectral image classification method based on Octave convolution, and solves the problems of large class spacing, small different class spacing and low classification accuracy in the prior art. The scheme is as follows: inputting images to be classified and preprocessing data, dividing a training set and a test set, constructing an Octave convolutional neural network, determining a loss function of the Octave convolutional neural network, training and updating the Octave convolutional neural network, testing the data of the test set, and completing hyperspectral image classification. According to the method, Octave convolution operation is used to reinforce feature representation, and a spatial attention mechanism and a spectral attention mechanism are introduced, so that the network can more accurately find an area which is more beneficial to classification and contains more comprehensive and detailed information. The method ishigh in classification precision and strong in robustness, and can be applied to analysis and management of hyperspectral image data.
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Description

Technical field

[0001] The invention belongs to the technical field of image processing, and particularly relates to the content classification of hyperspectral images. Specifically, it is a spatial spectrum attention hyperspectral image classification method based on Octave convolution, which can be applied to the analysis and management of hyperspectral image data. Background technique

[0002] With the continuous improvement of the pixel resolution of hyperspectral images, more useful data and information can be obtained from hyperspectral images. According to the needs of different applications, the processing of hyperspectral images also has different requirements. Therefore, in order to effectively analyze and manage these hyperspectral image data, it is necessary to attach a semantic label to each pixel of the hyperspectral image. The classification of hyperspectral images is an important way to solve such problems. Hyperspectral image classification refers to distinguish...

Claims

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