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Robust background estimation method-based local target detection method for hyperspectral image

A technology for hyperspectral image and background estimation, applied in the field of local target detection in hyperspectral images, can solve the problems of lack of stability, great influence of estimation results, and inability to deal with complex scenes well, so as to reduce the false alarm rate and improve the The effect of detection performance

Active Publication Date: 2015-02-11
NORTHWESTERN POLYTECHNICAL UNIV
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However, this method is greatly affected by the estimation results of outliers and objects of

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  • Robust background estimation method-based local target detection method for hyperspectral image
  • Robust background estimation method-based local target detection method for hyperspectral image
  • Robust background estimation method-based local target detection method for hyperspectral image

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[0027] The specific steps of the hyperspectral image local target detection method based on the robust background estimation method of the present invention are as follows:

[0028] The hyperspectral remote sensing image has a cubic structure. The spatial dimension reflects the reflectance of pixels corresponding to different positions on the ground in a certain sunlight band, and the spectral dimension reflects the reflectance of pixels at a certain position in different bands. A hyperspectral image can be represented as a p×n data set X n ={x 1 ,x 2 ,...,x n}, p is the number of bands, n is the total number of pixels in the image; a certain pixel in the image can be expressed as x i =(x 1i ,x 2i ,...,x pi ) T , x pi is the reflectivity at the pth band.

[0029] 1. Whiten the input data.

[0030] For the input hyperspectral image, use the MCD estimation method to estimate the global background parameters, and then whiten the input data to obtain the whitened data D w...

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Abstract

The invention discloses a robust background estimation method-based local target detection method for a hyperspectral image. The method is used for solving the technical problem of high false alarm rate of a conventional local target detection method for the hyperspectral image. According to the technical scheme, a spectral-angle-based clustering method is used for clustering an input image in a whitened space; in a detection process, an MCD estimation method for estimating a background parameter of a cluster to which a pixel to be detected belongs is introduced, so that the detection performance is improved; a target detection result on a dataset provided by the RIT (Rochester institute of technology) shows that an average score reflecting the false alarm rate is 2.8, and is lowered by 4.4 compared with that of an improved Halper method; a detection result on an AVIRIS (airborne visible infrared imaging spectrometer) database shot by a satellite shows that the false alarm rate is 0.11 percent under the detection rate of 100 percent, the false alarm rate of a Halper method is about 0.29 percent, and the false alarm rate of a global method is 0.82 percent, so that the false alarm rate is remarkably lowered.

Description

technical field [0001] The invention relates to a hyperspectral image local target detection method, in particular to a hyperspectral image local target detection method based on a robust background estimation method. Background technique [0002] Hyperspectral image is to use the imaging spectrometer to record the spectral information of various ground objects observed in the field of view to obtain image data. It combines the spatial and spectral information of ground materials, and provides fine spectral resolution for the classification and The detection provides a reliable basis. [0003] Most detection methods distinguish the target from the background by calculating the distance between the pixel to be tested and the mean value of the background, or by calculating the similarity between the pixel to be tested and the known characteristic spectrum of the target. Traditional unstructured target detection algorithms such as Adaptive Cosine / Coherence Estimator (ACE) are ...

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Application Information

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IPC IPC(8): G06T7/00
CPCG06V20/194G06V20/13G06V2201/07G06F18/232
Inventor 张艳宁魏巍严杭琦张磊李飞王波波
Owner NORTHWESTERN POLYTECHNICAL UNIV
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