Improved hyperspectral image classifying method

A hyperspectral image and classification method technology, applied in the direction of instruments, character and pattern recognition, computer components, etc., can solve the problems of the same spectrum of different objects, the same object of different spectra, etc., to ensure accurate description, strong discrimination, and meet the speed and the effect of different requirements on precision

Active Publication Date: 2016-09-21
NANJING NORMAL UNIVERSITY
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Problems solved by technology

[0005] In order to solve the technical problems of the same object with different spectra and different objects with the same spectrum in hyperspectral images, the present invention proposes a

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  • Improved hyperspectral image classifying method
  • Improved hyperspectral image classifying method

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Embodiment Construction

[0029] The specific embodiments of the present invention will be described below in conjunction with the accompanying drawings.

[0030] Such as figure 1 As shown, the present invention discloses an improved hyperspectral image classification method for hyperspectral image processing, the specific steps are as follows:

[0031] Step 1, the spatial neighbor selection of the image center pixel point: the spatial feature in the spectral-space joint classification under the spatial preprocessing method is the basic guarantee for the final high-quality classification, and the spatial feature depends on the spatial neighbor selection. The present invention focuses on mining and utilizing spatial information. Obtain spatial information features that can better describe the central pixel, and focus on efficiency and accuracy to meet actual needs, paving the way for step 2.

[0032] Step 2, extract the spatial features of the central pixel: Through step 1, the high-quality spatial nei...

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Abstract

The invention discloses an improved hyperspectral image classifying method comprising the following steps of: (1) selecting the spatial neighbor of the central pixel of a hyperspectral image to be classified to obtain a high-quality spatial neighbor area by using a selection strategy based on watershed segmentation area or a minimal spanning tree neighbor selection strategy; (2) extracting the spatial feature of the high-quality spatial neighbor area; and (3) predicting a spectral space joint model to fuse a spatial feature and a spectral feature in a synthetic kernel way, to train a classification model, and to predict a hyperspectral image test set tag. The method selects different spatial neighbor selection modes, satisfies requirement for speed and precision in hyperspectral classification, solves a problem of same object with different spectra and different objects with same spectrum in the hyperspectral image by mining and utilizing spatial information, enhances the robustness of the original spectrum classification in virtue of high-quality spatial neighbor and feature information, and has a high use value.

Description

technical field [0001] The invention belongs to the field of hyperspectral image processing, in particular to an improved hyperspectral image classification method. Background technique [0002] With the continuous development of remote sensing hardware, hyperspectral remote sensing image processing technology has been developed rapidly and widely used, attracting the attention of a large number of researchers. Traditional remote sensing image classification only uses less band spectral information, while hyperspectral images contain hundreds of band spectral information, which is more helpful for classification, but classical pattern recognition methods classify them, and the misclassification phenomenon is less Seriously, the effect is not ideal. [0003] The rich spectral information in hyperspectral images also contains many challenges and problems, such as high-dimensional small sample classification, same object with different spectra, same spectrum with different obj...

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Application Information

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IPC IPC(8): G06K9/62
CPCG06F18/24147G06F18/253
Inventor 杨明赵振凯
Owner NANJING NORMAL UNIVERSITY
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