Hyperspectral image classification method and device based on spatial-spectral dimension filtering

Abstract

The invention relates to the field of hyperspectral image processing, in particular to a hyperspectral image classification method and device based on space spectral dimension filtering. According tothe method and the device, TSG filtering and black and white mask calibration are carried out on a hyperspectral image of a sample after reflectivity inversion; and constructing a feature set based onthe label information of the hyperspectral image of the sample and the first multiple principal components of the hyperspectral image of the sample, inputting the feature set into a training set to train a support vector machine, and classifying a test set by using the trained support vector machine. According to the method and the device, the hyperspectral image is constructed by combining principal component analysis and a support vector machine algorithm, so that DN value distortion caused by the influence of the three-dimensional form of a sample in the hyperspectral image can be inhibited, meanwhile, the strip noise of the spectral dimension of the image is improved, and the spatial-spectral dimension filtering of the hyperspectral image is realized. According to the method, DN valuedistortion caused by sample edges and irregular surfaces in the hyperspectral images is improved, the classification precision of the images is effectively improved, and the method and device can beapplied to the fields of agriculture, pharmaceutical industry, environmental monitoring and the like.

Description

technical field [0001] The present invention relates to the field of hyperspectral image processing, in particular to a hyperspectral image classification method and device based on spatial spectral dimension filtering. Background technique [0002] Hyperspectral images have target area space and spectral information, and are widely used in agriculture, environmental monitoring, ground object detection and other fields. In the process of hyperspectral image acquisition, due to the influence of the three-dimensional shape of the target sample, the edge of the image and some irregular surfaces will cause uneven illumination to varying degrees, resulting in the distortion of the DN value in the hyperspectral image, and the DN value (Digital Number ) is the brightness value of the pixel in the remote sensing image, and the gray value of the recorded ground object. These distortions will affect the spectral characteristics of the sample points in the image to a certain extent, an...

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Problems solved by technology

[0004] Embodiments of the present invention provide a hyperspectral image classification method and device based on spatial spectral dimension filtering, to at least solve the classification accuracy caused by the DN value distortion caused by the sample edge and irregular surface in the hyperspectral image in the prior art poor technical problem

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