Hyperspectral image classification method based on multi-classifier combination

Abstract

The invention discloses a hyperspectral image classifying method based on multi-classifier combining, and belongs to the technical field of the combination of remote sensing imaging and mode recognizing. The hyperspectral image classifying method based on the multi-classifier combining comprises the first step of selecting a plurality of sets of good waveband subsets from all wavebands of a hyperspectral image, the second step of building corresponding character spaces based on all selected waveband subsets and training classifiers in the character spaces built based on the waveband subset sets through hyperspectral image training samples to obtain a plurality of basic classifiers corresponding to the waveband subsets in a one-to-one mode, and the third step of classifying the hyperspectral image training samples in a classifier combining mode according to the basic classifiers. The multi-classifier combining thought is introduced into hyperspectral waveband selecting, and compared with the prior art, the classifying accuracy obtained after waveband selection can be effectively improved.

Description

Technical field [0001] The invention relates to a hyperspectral band selection method, in particular to a hyperspectral image classification method based on a combination of multiple classifiers, and belongs to the technical field of combining remote sensing imaging and pattern recognition. Background technique [0002] With the development of remote sensing technology and imaging spectrometers, the resolution of hyperspectral images has been continuously improved, and the application requirements have become more and more extensive. However, its characteristics of large number of bands and huge data volume have brought the classification and recognition of hyperspectral images. Great difficulty. The use of all band data for classification and other processing is not only difficult, but also due to the existence of a large amount of redundant information and the influence of some noise bands or bands with low signal-to-noise ratio data will also reduce the classification or recog...

AI Technical Summary

Problems solved by technology

[0005] The technical problem to be solved by the present invention is to overcome the disadvantage of discarding more identification information in the prior art, resulting in low classification accuracy after band selection, and to introduce the idea of ​​multi-classifier combination into hyperspectral band selection to provide a method based on A hyperspectral image classification method based on a combination of multi-classifiers can effectively improve the classification accuracy after band selection

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