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High spectral image target detection method based on high order statistic

A hyperspectral image and high-order statistics technology, which is applied in image enhancement, image analysis, image data processing, etc., can solve the problem of not using high-order statistics of data, achieve good detection effect and improve the detection probability

Active Publication Date: 2010-08-18
BEIHANG UNIV
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Problems solved by technology

[0005] These existing target detection methods mainly use the second-order statistics of the data for calculation, mainly involving the covariance matrix or correlation matrix of the data, but do not use the high-order statistics of the data

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  • High spectral image target detection method based on high order statistic
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  • High spectral image target detection method based on high order statistic

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Embodiment Construction

[0053] In order to better understand the technical solution of the present invention, the embodiments of the present invention will be further described below in conjunction with the accompanying drawings:

[0054] The present invention is realized under the MATLAB R2008b language environment. After the computer reads the hyperspectral remote sensing image data, it obtains a data cube. First, the data is de-averaged to make the mean value of the data zero, and then the data is whitened to remove the correlation of the data. The detection process can be regarded as a filtering process. Spectral curve x=[x 1 , x 2 ,...,x M ] T As the input of the filter, the filter weight vector w=[w 1 ,w 2 ,...,w M ] T and the product w of the input x T x as output. Set the high-order statistics of the output data as the objective function, and find the optimal weight vector w, so that under the constraint that the gain of the known target spectrum is 1, the high-order statistics of t...

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Abstract

The invention relates to a high spectral image target detection method based on high order statistics, which comprises the following steps: (1) reading data of a high spectral image in the environment of MATLAB R2008b by a computer; (2) preprocessing (i.e. de-equalization and whitening) the data by the computer; (3) constructing high order statistics for minimizing output data under the constraint that the spectral gain of the detection filter for the target is 1, and solving the optimal weight vector of the detection filter; and (4) setting an appropriate threshold, and acquiring the detection result image. The invention overcomes the defects in the prior art, and has good detection effect by fully utilizing the high order statistics of the data. In particular, the invention can enhance the detection probability on the premise of low false alarm rate. Thus, the invention has high practical value and wide application prospects in the technical field of target detection of high spectral remote sensing images.

Description

(1) Technical field: [0001] The invention relates to a hyperspectral image target detection method based on high-order statistics, and belongs to the technical field of hyperspectral remote sensing image target detection. (two) background technology: [0002] With the rapid development of hyperspectral imaging technology in the past three decades, the analysis and processing methods of hyperspectral images have become one of the research hotspots in the field of remote sensing images at home and abroad. Compared with traditional remote sensing images, hyperspectral images are characterized by high spectral resolution, which can obtain image information of dozens or even hundreds of spectral bands of observed objects. The width of the continuous wave band obtained by the imaging spectroscopy system is generally within 10nm, so this kind of data can distinguish those surface materials with diagnostic spectral characteristics with sufficient spectral resolution, which is also t...

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Application Information

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IPC IPC(8): G06T7/00G06T5/00G06K9/00
Inventor 史振威杨硕姜志国赵卫王扬
Owner BEIHANG UNIV
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