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The Classification Technology Research Based on Hyperspectral Data

Author: XieQiuChang
Tutor: HanLing
School: Chang'an University
Course: Photogrammetry and Remote Sensing
Keywords: Hyperspectral classification Endmember extraction Mixed pixel decomposition Pixel spatial characteristics Spectral angle mapping method
CLC: P237
Type: Master's thesis
Year: 2008
Downloads: 307
Quote: 6
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Abstract


In the nearly 20 years of development , hyperspectral remote sensing as a new type of remote sensing methods in multiple military and civilian areas play an important role , however how its generated large amounts of data quickly and accurately dig out the need information is still a need to solve difficult problems . In this paper, the characteristics of hyperspectral image data , the experimental study of the surface features a wealth of information extracted from hyperspectral data and effective classification . Thesis hyperspectral image classification and recognition for the target endmember extraction method based on hyperspectral data and mixed pixel decomposition model , combined pixel spatial characteristics of classification , and finally through the experiment comparison in the traditional classification technically traditional hyperspectral classification and classification techniques combined pixel spatial characteristics . To sum up , the paper mainly research work carried out in the following aspects : 1 , pure pixel index convex cone analysis method , and based on the RMS error analysis of hyperspectral endmember extraction algorithm , while taking advantage of the existing data on pure pixel index method and convex cone analysis of experimental analysis . 2, a detailed analysis of the current mixed pixel decomposition model theory , linear spectral mixture model , nonlinear spectral mixture model and fuzzy analysis model . End metadata the some solution mixed case , the depth of the hyperspectral data classification method , that is, the maximum likelihood classification , artificial neural network classification technology, and spectral angle mapping method . 4 , on the basis of previous studies , the proposed comparative analysis of to combine pixel space features high spectral classification and the experimental method and traditional hyperspectral classification method , by contrast analysis found that take full advantage of pixel space characteristics is an effective way to improve the image classification accuracy .

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CLC: > Astronomy,Earth Sciences > Surveying and Mapping > Photogrammetry and Surveying, Mapping and Remote Sensing > Surveying, Mapping and Remote Sensing technology
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