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Hyperspectral image waveband selecting method applying neural network to carry out sensitivity analysis

A technology of sensitivity analysis and band selection, applied in the field of hyperspectral remote sensing image processing, which can solve the problems of unclear model mechanism and troublesome application of sensitivity analysis methods.

Active Publication Date: 2015-06-24
HOHAI UNIV
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Problems solved by technology

Sensitivity analysis methods can only be realized based on specific models. However, in most cases, when people face massive data information, they do not know what the internal model mechanism of these data is, which gives sensitivity analysis methods further app is causing trouble

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  • Hyperspectral image waveband selecting method applying neural network to carry out sensitivity analysis
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  • Hyperspectral image waveband selecting method applying neural network to carry out sensitivity analysis

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Embodiment Construction

[0042] Below in conjunction with specific embodiment, further illustrate the present invention, should be understood that these embodiments are only used to illustrate the present invention and are not intended to limit the scope of the present invention, after having read the present invention, those skilled in the art will understand various equivalent forms of the present invention All modifications fall within the scope defined by the appended claims of the present application.

[0043] Such as image 3 As shown, the hyperspectral image band selection method using neural network sensitivity analysis includes the following steps:

[0044] Step 1: Data preprocessing. Eliminate the interference bands, pre-select the types of ground objects, use the adaptive subspace (ASD) method to divide the band set of hyperspectral remote sensing images, and then select the number of bands in each subspace according to the ratio Rs to form a band combination, combined with the pre-selecte...

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Abstract

The invention discloses a hyperspectral image waveband selecting method applying a neural network to carry out sensitivity analysis. The method comprises the steps that firstly, a subspace dividing method is used for predicting some waveband combinations with the poor relevancy, a training sample and a testing sample are determined according to a pre-selected surface feature type and original surface feature information, and a BP neural network topology structure is determined; secondly, the BP neural network is optimized through a differential evolution algorithm; finally, the Ruck sensitivity analysis is executed through the optimized BP neural network, sensitivity analysis results of all testing sampling points are integrated through a comprehensive judgment function, and the waveband having the greatest effect on the classification result is finally screened out.

Description

technical field [0001] The invention relates to a method for selecting bands of hyperspectral remote sensing images, in particular to a method for selecting bands of hyperspectral remote sensing images using neural network sensitivity analysis, and belongs to the technical field of hyperspectral remote sensing image processing. Background technique [0002] Remote Sensing (Remote Sensing) is a technology that uses the principle of electromagnetic waves to obtain distant signals and image them, and can feel and perceive distant things remotely. It is a new science. With the improvement of computer technology and optical technology, remote sensing technology has also been developed rapidly. In recent years, a variety of remote sensing satellites have been successfully launched, which has promoted the remote sensing data acquisition technology towards three high (high spatial resolution, high spectral resolution and high temporal resolution) and three multi (multi-platform, mul...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06N3/08
Inventor 李臣明高红民王艳陈玲慧史宇清何振宇
Owner HOHAI UNIV
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