Hyperspectral remote sensing image classifying and recognizing method

A hyperspectral remote sensing and hyperspectral image technology, which is applied in the field of remote sensing image classification and recognition, can solve the problem of low classification accuracy

Active Publication Date: 2013-12-11
NORTHWESTERN POLYTECHNICAL UNIV
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Problems solved by technology

[0004] In order to overcome the deficiency of low classification accuracy of existing hyperspectral remote sensing image classification methods based on sparse representation and spectral information, the present invention provides a hyperspectral remote sensing image classification and recognition method

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  • Hyperspectral remote sensing image classifying and recognizing method
  • Hyperspectral remote sensing image classifying and recognizing method
  • Hyperspectral remote sensing image classifying and recognizing method

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Embodiment Construction

[0032] The specific steps of the hyperspectral remote sensing image classification and recognition method of the present invention are as follows:

[0033] 1. Generate a sparse representation dictionary.

[0034] Input the training sample set, first construct the sparse representation dictionary. There are training samples of class C features, where the c-th class features have n c pixels, then the c-th class training samples are expressed in the following matrix form:

[0035] D c = [ d c , 1 , d c , 2 , . . . , d c , n c ] , ∈ R ...

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Abstract

The invention discloses a hperspectral remote sensing image classifying and recognizing method which is used for solving the technical problem that an existing hperspectral remote sensing image classifying method based on sparse representation and spectrum information is low in precision. According to the technical scheme, by means of combination of a word bag model and hperspectral remote sensing image data, various professional dictionaries are generated, a sparse representation dictionary is further constructed, then sparse representation characteristics of image elements are calculated according to the dictionary, sparse representation coefficients of the image elements are restricted in a space dimension by means of space continuity, and finally hperspectral image classification is achieved by solving an optimization problem. Representational capacity of the generated dictionary is relatively strong, and space structure information of hperspectral images is fully considered, so that classification precision is improved. The AVIRIS hperspectral images are classified, the overall classification precision is improved from 82.58% in the prior art to 86.87%, processing time is shortened from 97.469 seconds in the prior art to 35.539 seconds, and efficiency is improved by nearly three times.

Description

technical field [0001] The invention relates to a remote sensing image classification and recognition method, in particular to a hyperspectral remote sensing image classification and recognition method. Background technique [0002] In recent years, high-resolution remote sensing sensors at home and abroad have developed rapidly. High-resolution earth observation systems have become the frontier of high-tech development in the world. High-resolution remote sensing image analysis is also of great significance to the development of military and civilian applications. Hyperspectral remote sensing images are three-dimensional data cubes composed of dozens or even hundreds of continuous band images. possible. The hyperspectral remote sensing image classification and recognition technology is an important part of the high-resolution earth observation system. It provides us with in-depth exploration of geophysical and chemical characteristics, fine identification of small differen...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62
Inventor 张艳宁魏巍任越美张磊孟庆洁佘红伟张秀伟李飞
Owner NORTHWESTERN POLYTECHNICAL UNIV
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