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Hyperspectral remote sensing image waveband selection method based on firefly optimization

A technology for hyperspectral remote sensing and firefly optimization, which is applied in the field of hyperspectral remote sensing image band selection, and can solve the problems of low precision and time-consuming hyperspectral remote sensing bands.

Inactive Publication Date: 2014-09-03
HOHAI UNIV
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  • Application Information

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Problems solved by technology

[0006] Purpose of the invention: Aiming at the problems and deficiencies in the above-mentioned prior art, the purpose of the present invention is to provide a hyperspectral remote sensing image band selection method based on firefly optimization to solve the problem of low precision and time-consuming hyperspectral remote sensing band selection

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  • Hyperspectral remote sensing image waveband selection method based on firefly optimization
  • Hyperspectral remote sensing image waveband selection method based on firefly optimization
  • Hyperspectral remote sensing image waveband selection method based on firefly optimization

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Embodiment

[0034] Example: The experimental data is a hyperspectral image of Washington DC acquired by a HYDICE (Hyperspectral Digital Imagery Collection Experiment) sensor. The data covered 210 bands in the spectral range from 0.4 to 2.5um, and its spatial resolution was about 2.8m; after removing water absorption bands and noise bands, 191 bands were reserved for data analysis. The experimental data is a sub-image cut from the original image of DC Mall. The data size is 266×304, including 7 categories including Road, Grass, Water, Trail, Tree, Shadow and Roof.

[0035] Such as figure 1 As shown, the specific implementation steps are:

[0036] (1) Perform data preprocessing on the original hyperspectral remote sensing image data, remove noise bands, and then determine typical spectral data and training sample data. Randomly initialize N fireflies, let N=30;

[0037](2) Randomly initialize N groups of the same number of band combinations, the size of the combination matrix is ​​s, th...

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Abstract

The invention discloses a hyperspectral remote sensing image waveband selection algorithm based on improving firefly algorithm, and object functions in the FA algorithm are improved. Optimization and improvement of waveband selection is characterized by carrying out random initialization on waveband index position, position matrix size being s=n*b (n being known parameters, b being user-input waveband selection number); selecting different spectrum type distance function as the object function, substituting the obtained initial position matrix into the object function for calculation, and obtaining a group of one-dimensional array corresponding to the fluorescence brightness values of fireflies; carrying out ranking (disadvantaged point approaching to advantaged point) according to the advantages and disadvantages of the brightness values, that is, the value of the object function value; updating the waveband which is subjected to feature selection, that is, the position information of the fireflies after movement; and recording the waveband selection results when according with maximum iterations or searching precision. According to the hyperspectral remote sensing image waveband selection method based on firefly optimization, the problems that a conventional hyperspectral remote sensing image waveband selection algorithm is not high in precision and time-consuming can be solved; and the method has the advantages of being good in waveband selection effect, and wide in adaptation and the like.

Description

technical field [0001] The invention relates to a hyperspectral remote sensing image band selection method based on firefly optimization, and belongs to the technical field of hyperspectral remote sensing image processing. Background technique [0002] Hyperspectral remote sensing, also known as Imaging Spectroscopy, refers to the technology of using many narrow electromagnetic wave bands to obtain data about objects. It is one of the major technological breakthroughs in earth observation in the last 20 years of the 20th century. And the frontier technology of remote sensing in the next few decades. It utilizes the nanoscale spectral resolution of the imaging spectrometer to obtain a lot of very narrow and spectrally continuous image data, and realizes the simultaneous acquisition of surface object space, radiation, and spectral information; thus providing tens to hundreds of narrow bands for each pixel (wavelength less than 10nm) spectral information, generate a complete a...

Claims

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Application Information

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IPC IPC(8): G06K9/62
Inventor 苏红军李茜楠
Owner HOHAI UNIV
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