Spectropolarimetric bidirectional reflectance distribution modeling for background based on LS-SVM regression

Yong Qiang Zhao; Dan Liu; Chao Chen; Yong Mei Cheng

doi:10.3788/gzxb20114010.1494

Spectropolarimetric bidirectional reflectance distribution modeling for background based on LS-SVM regression

Yong Qiang Zhao, Dan Liu, Chao Chen, Yong Mei Cheng

School of Automation

Northwestern Polytechnical University Xian

Research output: Contribution to journal › Article › peer-review

4 Scopus citations

Abstract

Relationship between detection geometry and spectropolarimetric bidirectional reflectance distribution function for soil background was analyzed in detail. The modeling of spectropolarimetric bidirectional reflectance distribution function was proposed based on LS-SVM, aiming to extend the value of measured spectropolarimetric bidirectional reflectance distribution function with limited geometry to whole hemi-sphere space. Results show that the predicted value and experimental value are close and meet the need of correction.

Original language	English
Pages (from-to)	1494-1499
Number of pages	6
Journal	Guangzi Xuebao/Acta Photonica Sinica
Volume	40
Issue number	10
DOIs	https://doi.org/10.3788/gzxb20114010.1494
State	Published - Oct 2011

Keywords

Detection geometry
LS-SVM Regression
Spectropolarimetric bidirectional reflectance distribution function

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title = "Spectropolarimetric bidirectional reflectance distribution modeling for background based on LS-SVM regression",

abstract = "Relationship between detection geometry and spectropolarimetric bidirectional reflectance distribution function for soil background was analyzed in detail. The modeling of spectropolarimetric bidirectional reflectance distribution function was proposed based on LS-SVM, aiming to extend the value of measured spectropolarimetric bidirectional reflectance distribution function with limited geometry to whole hemi-sphere space. Results show that the predicted value and experimental value are close and meet the need of correction.",

keywords = "Detection geometry, LS-SVM Regression, Spectropolarimetric bidirectional reflectance distribution function",

author = "Zhao, {Yong Qiang} and Dan Liu and Chao Chen and Cheng, {Yong Mei}",

year = "2011",

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volume = "40",

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AU - Zhao, Yong Qiang

AU - Liu, Dan

AU - Chen, Chao

AU - Cheng, Yong Mei

PY - 2011/10

Y1 - 2011/10

N2 - Relationship between detection geometry and spectropolarimetric bidirectional reflectance distribution function for soil background was analyzed in detail. The modeling of spectropolarimetric bidirectional reflectance distribution function was proposed based on LS-SVM, aiming to extend the value of measured spectropolarimetric bidirectional reflectance distribution function with limited geometry to whole hemi-sphere space. Results show that the predicted value and experimental value are close and meet the need of correction.

AB - Relationship between detection geometry and spectropolarimetric bidirectional reflectance distribution function for soil background was analyzed in detail. The modeling of spectropolarimetric bidirectional reflectance distribution function was proposed based on LS-SVM, aiming to extend the value of measured spectropolarimetric bidirectional reflectance distribution function with limited geometry to whole hemi-sphere space. Results show that the predicted value and experimental value are close and meet the need of correction.

KW - Detection geometry

KW - LS-SVM Regression

KW - Spectropolarimetric bidirectional reflectance distribution function

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U2 - 10.3788/gzxb20114010.1494

DO - 10.3788/gzxb20114010.1494

M3 - 文章

AN - SCOPUS:82555182329

SN - 1004-4213

VL - 40

SP - 1494

EP - 1499

JO - Guangzi Xuebao/Acta Photonica Sinica

JF - Guangzi Xuebao/Acta Photonica Sinica

IS - 10

ER -

Spectropolarimetric bidirectional reflectance distribution modeling for background based on LS-SVM regression

Abstract

Keywords

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