Hyperspectral image classification method based on context-rich networks

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United States of America Patent

PATENT NO 11941865
APP PUB NO 20230334829A1
SERIAL NO

18337444

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Abstract

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Disclosed in the present invention is hyperspectral image classification method based on context-rich networks. The method comprises a training stage and a prediction stage, wherein the training stage comprises image pre-processing, sample selection and network training. Firstly, performing normalization on a hyperspectral image, and then randomly selecting an appropriate proportion of marked samples from each category to generate a label map, and performing training by using the designed network; in the prediction stage, directly inputting the whole image into the trained network and obtaining a final classification result. By means of the present invention, data pre-processing, feature extraction, the process of context-rich information capturing, and classification are taken into comprehensive consideration in the whole flow; and the classification of a hyperspectral image is realized by means of constructing an end-to-end network.

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Patent Owner(s)

  • WUHAN UNIVERSITY

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Inventor(s)

Inventor Name Address # of filed Patents Total Citations
Du, Bo Hubei, CN 35 118
Wang, Di Hubei, CN 165 543
Zhang, Liangpei Hubei, CN 3 1

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