GPU-based parallel realizing method of abundance estimation algorithm

An implementation method and abundance estimation technology, applied in the field of GPU parallel processing, can solve the problems of slow software operation and difficult hardware implementation, and achieve the effect of improving operation efficiency

Inactive Publication Date: 2018-01-30
DALIAN MARITIME UNIVERSITY
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Problems solved by technology

The implementation of traditional algorithms (such as least square error and orthogonal subspace projection) usually involves a large number of matrix inversion and multi

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  • GPU-based parallel realizing method of abundance estimation algorithm
  • GPU-based parallel realizing method of abundance estimation algorithm
  • GPU-based parallel realizing method of abundance estimation algorithm

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[0041] In order to make the purpose, technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the implementation of the present invention. example, not all examples. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0042] Such as figure 1 A parallel implementation method of a GPU-based abundance estimation algorithm is shown, comprising the following steps:

[0043] Step 1. Store the hyperspectral mixed pixel data H to the GPU side, that is, copy it to the GPU memory through the communication function cudamemcpy, and the hyperspectral data is expressed as H={B 1 ,B 2 ,,...

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Abstract

The invention discloses a GPU-based parallel realizing method of an abundance estimation algorithm. The GPU-based parallel realizing method comprises the steps of: 1, storing hyperspectral mixed pixeldata H to a GPU end; 2, acquiring end element vectors m, and allocating the acquired end element vectors m to p parallel threads on a CPU side one by one; 3, acquiring vectors m<~> which correspond to the end element vectors m and are orthogonal in a vector space [m<1>, m<2>, ..., m<i-1>]; 4, acquiring an orthogonal basis corresponding to an end element set M, and calculating a corresponding inner product value; 5, calculating projection of a spectral vector of each pixel in a d<~T> direction; 6, and calculating an abundance result alpha p corresponding to each end element mp, andstoring the abundance result alpha p to the GPU end. According to the GPU-based parallel realizing method, the abundance value is calculated by adopting a GPU parallel processing kernel function, theparallel mechanism runs much faster than on the traditional CPU serial mechanism, and the operating efficiency of real-time abundance estimation is greatly improved.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a GPU parallel processing method for hyperspectral image abundance value estimation methods, so as to improve fast calculation of real-time hyperspectral abundance. Background technique [0002] Hyperspectral remote sensing technology aims to obtain ground object information in tens to hundreds of continuous fine spectral bands, and has been widely used in many fields such as environment, national defense, agriculture, and deep space. Abundance estimation is one of the most important topics in hyperspectral technology. Its purpose is to obtain the corresponding percentage (ie, abundance value) of the corresponding endmember in each mixed pixel after the endmember extraction is completed. The implementation of traditional algorithms (such as least square error and orthogonal subspace projection) usually involves a large number of matrix inversion and multiplic...

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Application Information

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IPC IPC(8): G06T1/20
Inventor 宋梅萍于纯妍武平张建祎
Owner DALIAN MARITIME UNIVERSITY
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