Simplex triangular decomposition-based method for decomposing mixed pixels of hyperspectral remote sensing images

A technology of hyperspectral remote sensing and triangular decomposition, which is applied in the field of hyperspectral remote sensing data mixed pixel decomposition, and can solve problems such as multi-calculation time, high computational complexity, and consumption

Inactive Publication Date: 2011-05-11
FUDAN UNIV
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Problems solved by technology

Both N-FINDR and SGA search for endmembers by maximizing the volume of the simplex, but directly calculating the volume

Method used

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  • Simplex triangular decomposition-based method for decomposing mixed pixels of hyperspectral remote sensing images
  • Simplex triangular decomposition-based method for decomposing mixed pixels of hyperspectral remote sensing images
  • Simplex triangular decomposition-based method for decomposing mixed pixels of hyperspectral remote sensing images

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Embodiment Construction

[0180] In the following, we respectively use simulation data and actual remote sensing image data as examples to illustrate specific implementation methods.

[0181] 1 simulation data

[0182] The SVATF method proposed by the present invention is compared with the following three typical algorithms: HOS-ICPA[6], VCA[4], and MVCNMF[7]. Among them, the VCA algorithm can only obtain the spectral matrix, so we use FCLS[8] to obtain the abundance matrix after solving the spectrum, and record this method as VCA-FCLS. We use simulation data to test the performance of all the above algorithms, and use SAD and RMSE to measure the difference between the results of all algorithms and the real reference values.

[0183] Spectral Angle Distance (Spectral Angle Distance, SAD) is used to measure the degree of difference between the spectrum solved by the algorithm and the known reference spectrum, the real spectral vector a of the i-th end member i =[a i1 , a i2 ,...,a iL ] T The corre...

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Abstract

The invention belongs to the field of remote sensing image processing technology, and particularly relates to a simplex triangular decomposition-based method for decomposing mixed pixels of hyperspectral remote sensing images. The method adopts a linear mixture model, and comprises the two steps: end member extraction and abundance estimation. The method not only is a geometric method based on simplex, and meanwhile is based on the algebraic principle of triangular decomposition. The triangular decomposition adopts either Cholesky decomposition or QR decomposition, and can improve the search efficiency of an end member during the process of end member extraction through recursive operation. The method can effectively extract the end member from hyperspectral remote sensing data, thereby solving the problem in decomposing mixed pixels. The method has a specifically important application value in the hyperspectral remote sensing image-based high-precision surface feature classification as well as the inspection and identification of ground targets.

Description

technical field [0001] The invention belongs to the technical field of remote sensing image processing, and in particular relates to a method based on a triangular decomposition algorithm, which can solve the problem of hyperspectral remote sensing data mixed pixel decomposition. Background technique [0002] Remote sensing is a new comprehensive technology developed in the 1960s. It is closely related to science and technology such as space, electron optics, computer, and geography. It is one of the most powerful technical means for studying the earth's resources and environment. In recent years, with the advancement of imaging technology, multi-band remote sensing images have been widely used in more and more fields. Due to the limitation of the spatial resolution of the imaging system and the complexity and variety of the surface, a pixel in the obtained remote sensing image often contains multiple types of ground objects, which forms a mixed pixel. How to extract the sp...

Claims

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Application Information

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IPC IPC(8): G06T7/00
Inventor 夏威王斌张立明
Owner FUDAN UNIV
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