Spatial spectrum fusion hyperspectral image classification method based on a three-dimensional deep residual network

Abstract

The invention belongs to the field of hyper-spectral intelligent perception, and particularly discloses a spatial spectrum fusion hyper-spectral image classification method based on a three-dimensional deep residual network, which comprises the following steps: S1, generating candidate frames by using a sliding window method, and generating a plurality of windows; S2, randomly dividing the windowinto a training set and test set data; S3, training a three-dimensional depth residual network (3D-CNN) based on the hyperspectral data in the training set; S4, inputting a test set sample into the classification model, The hyperspectral image classification method has the advantages that the characteristics of the input data are extracted and predicted, the spectral characteristics and the spatial spectrum characteristics of the hyperspectral image are extracted at the same time, the classification precision of the hyperspectral image is further improved, a residual network structure is introduced, and the problem of learning degradation in a traditional hyperspectral classification neural network is solved. The hyperspectral image target classification method is clear in structure and easy to implement, the structural characteristics of the hyperspectral image can be fully utilized, and the hyperspectral image target classification precision is remarkably improved while the calculation time is shortened.

Description

technical field [0001] The invention belongs to the field of hyperspectral intelligent perception, and relates to a space-spectrum fusion hyperspectral image classification method based on a three-dimensional deep residual network, which can be used for target classification of hyperspectral images. Background technique [0002] A hyperspectral image is an image captured by an imaging spectrometer, which simultaneously describes the two-dimensional spatial information of the target distribution and the one-dimensional spectral information of the target spectral characteristics, and provides tens or even hundreds of narrow-band spectral information for each pixel. Produce a complete and continuous spectral curve. The hyperspectral image integrates the spectral information reflecting the target radiation and the image information reflecting the two-dimensional space of the target, realizing the "integration of map and spectrum", which is an image cube of two-dimensional graphi...

AI Technical Summary

Problems solved by technology

[0006] The present invention aims at the shortcomings of the traditional space-spectrum joint classification method, such as the complex implementation and the large impact of artificial preset features on the classification results, and integrates the "double high characteristics" of spatial information and spectral information, thereby obtaining a new three-dimensional deep residual network structure

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