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Hyperspectral image nonlinear unmixing method based on neural network

A hyperspectral image, neural network technology, applied in neural learning methods, biological neural network models, image data processing, etc.

Inactive Publication Date: 2019-10-25
TIANJIN UNIV
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For training neural networks, there is no clear method, which means that the user must train many times to find a good parameter setting

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  • Hyperspectral image nonlinear unmixing method based on neural network
  • Hyperspectral image nonlinear unmixing method based on neural network
  • Hyperspectral image nonlinear unmixing method based on neural network

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[0082] The present invention selects the hyperspectral image taken by the AVRIS sensor in the Moffett area of ​​Nevada, USA in 1997 as the test object. Since the original image is too large and the computational complexity is high, 50×50 sub-image blocks are selected for the experiment. It originally contains 189 bands, and the band ranges from 401 to 889 nm, such as figure 2 shown.

[0083] From the hyperspectral data used, the spectral curves of the three main surface covers of water (Water), soil (Soil) and vegetation (Vegetation) are obtained, such as image 3 shown. The endmember spectral curve extracted by VCA is basically consistent with the real endmember curve and can be used as the real value.

[0084] The present invention uses real data experiments to verify the algorithm performance, and the experiments use reconstruction error (Reconstruction Error, RE) and spectral angle distance (Spectral Angle Mapper, SAM) to evaluate the reconstruction performance of the pre...

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Abstract

The invention belongs to the technical field of image processing, and provides a hyperspectral image nonlinear unmixing method based on a neural network, which can effectively complete the work of extracting endmembers and obtaining endmember abundance and nonlinear coefficients, so that the unmixing effect can be further improved. improvement. The present invention: a hyperspectral image nonlinear unmixing method based on a neural network, comprising the following steps: (1): input hyperspectral image data; (2): randomly generating a sufficient number of training samples and test samples; (3): using The trained multi-layer perceptron neural network extracts the abundance and nonlinear coefficient of a single pixel in the hyperspectral image; (4): Make the obtained abundance meet the corresponding constraints; (5): Repeat for all Stop calculation after the pixels are unmixed; otherwise, return to step (3); (6): evaluate the algorithm performance of the invention by calculating the reconstruction error and spectral angular distance. The invention is mainly applied to image processing.

Description

technical field [0001] The invention belongs to the technical field of image processing, and relates to a hyperspectral image unmixing method, in particular to a hyperspectral image unmixing method based on a neural network. Background technique [0002] With the development of science and technology, remote sensing and earth observation technology has become increasingly mature, and has gradually become one of the important means of obtaining spatial geographic information. However, due to the limitation of the spatial resolution of the hyperspectral imager and the complexity of natural objects, some pixels of the obtained remote sensing images may be a mixture of several different material spectra, that is, mixed pixels. How to effectively realize the decomposition of mixed pixels has become an important direction of remote sensing research. The accurate decomposition of mixed pixels has important application value for high-precision ground object classification and groun...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00G06N3/08G06T3/40
CPCG06N3/08G06T3/4069G06V20/13
Inventor 李锵王旭陈雷张立毅刘静光
Owner TIANJIN UNIV
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