A Hyperspectral Image Classification Method Based on Label Constrained Elastic Net Graph Model
A technology of hyperspectral image and classification method, which is applied in the field of image information processing to achieve the effect of accurate composition and reduced computational complexity
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[0032] The technical solutions of the present invention will be described in detail below in conjunction with the accompanying drawings.
[0033] The present invention designs a hyperspectral image classification method based on a label-constrained elastic network graph model, such as figure 1 As shown, the steps are as follows:
[0034] S101, performing EMP feature extraction on the hyperspectral image to be treated, and constructing a space-spectrum joint feature;
[0035] S102. Perform label constraint transfer according to the space-spectrum joint feature to obtain a global constraint matrix;
[0036] S103. Construct a dictionary for each pixel according to the global constraint matrix;
[0037] S104, solving the elastic net representation according to the dictionary, and constructing a label-constrained elastic net graph model;
[0038] S105. Perform semi-supervised classification based on the elastic network graph model, obtain a label matrix, and realize hyperspectra...
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Abstract
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