Projection structure sparse coding-based hyperspectral image classification method

A hyperspectral image, sparse coding technology, applied in the field of hyperspectral image classification, can solve the problems of insufficient use of neighborhood information, limited classification accuracy, and easy existence of errors.

Active Publication Date: 2015-08-26
XIDIAN UNIV
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Problems solved by technology

However, this classification method is carried out separately for dimension reduction and classification, which is prone to errors and limits the classifi...

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  • Projection structure sparse coding-based hyperspectral image classification method
  • Projection structure sparse coding-based hyperspectral image classification method
  • Projection structure sparse coding-based hyperspectral image classification method

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Embodiment Construction

[0038] The present invention will be described in further detail below in conjunction with the accompanying drawings.

[0039] refer to figure 1 , the concrete steps of the present invention are as follows:

[0040] Step 1, input hyperspectral image.

[0041] Input a hyperspectral image to be classified that contains k categories, set each pixel of the hyperspectral image as a sample, and each sample is represented by its band feature to form a feature vector, m is the number of bands of the hyperspectral image .

[0042] Step 2, determine the training samples and test samples.

[0043] (2a) Using the method of equal probability sampling, randomly select 10% of the samples in the labeled spectral vector of the hyperspectral image as the training samples, for any sample x in the training samples i , define a i 5×5 spatial window as the center, to obtain hyperspectral image training image block X i ;

[0044] (2b) Take the remaining 90% of the samples as the test samples ...

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Abstract

The invention discloses a projection structure sparse coding-based hyperspectral image classification method, which mainly solves the problem that in the prior art, neighborhood information of a hyperspectral image can not be effectively used for classification. The method comprises the realizing steps of: (1) reading in hyperspectral image data; (2) determining a training sample set and a test sample set in spectral vectors with labels of the hyperspectral image; (3) solving a projection matrix according to the training sample set; (4) according to the projection matrix of training samples of the hyperspectral image, solving a sparse coefficient of the test sample set; (5) according to the projection matrix and the sparse coefficient of the test sample set, judging a test sample by using an error judgment function, thus obtaining a surface feature category label of the test sample. The method has the advantages of high classification precision, small processing expenditure cost of high dimensional data and usage for surface feature differentiation of the hyperspectral image.

Description

technical field [0001] The invention belongs to the technical field of remote sensing image processing, and in particular relates to a hyperspectral image classification method, which can be used to distinguish ground objects in hyperspectral images. Background technique [0002] Hyperspectral image object classification is the main content of remote sensing technology processing, based on the following: the same type of pixel has consistency in spectral characteristics and spatial characteristics, and different object types have obvious differences in spectral characteristics and spatial characteristics. Hyperspectral image is a mass data of map integration generated by multi-spectral remote sensing imaging equipment, which contains spatial information of ground objects and non-negative spectral information. Each point in the image can be described by a high-level spectral vector composed of spectral information of many spectral bands, so hyperspectral data is characterized...

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Application Information

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IPC IPC(8): G06K9/62
CPCG06F18/24143
Inventor 焦李成马文萍张风刘芳侯彪王爽杨淑媛
Owner XIDIAN UNIV
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