KPCA Algorithm for Hyperspectral Target/Anomaly Detection

Yanfeng Gu

doi:10.1002/9780470748992.ch15

KPCA Algorithm for Hyperspectral Target/Anomaly Detection

Yanfeng Gu^*

^*Corresponding author for this work

School of Electronics and Information Engineering, Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

1 Scopus citations

Original language	English
Title of host publication	Kernel Methods for Remote Sensing Data Analysis
Publisher	John Wiley & Sons, Ltd
Pages	353-373
Number of pages	21
ISBN (Print)	9780470722114
DOIs	https://doi.org/10.1002/9780470748992.ch15
State	Published - 4 Nov 2009
Externally published	Yes

Keywords

Curve of average local singularity and sequence number of nonlinear principal components
Hyperspectral images for numerical experiments
Hyperspectral images in civilian and military fields
KISD algorithm and processing flowchart
KPCA algorithm for hyperspectral target/anomaly detection
Kernel methods motivation for target and anomaly detection in hyperspectral images
Kernel-based anomaly detection in hyperspectral images
Kernel-based feature extraction in hyperspectral images
Kernel-based target detection in hyperspectral images
Target and anomaly detection - hyperspectral imagery applications

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10.1002/9780470748992.ch15

Cite this

@inbook{b3307b9444b3459e9da63c8a2f90a1e7,

title = "KPCA Algorithm for Hyperspectral Target/Anomaly Detection",

keywords = "Curve of average local singularity and sequence number of nonlinear principal components, Hyperspectral images for numerical experiments, Hyperspectral images in civilian and military fields, KISD algorithm and processing flowchart, KPCA algorithm for hyperspectral target/anomaly detection, Kernel methods motivation for target and anomaly detection in hyperspectral images, Kernel-based anomaly detection in hyperspectral images, Kernel-based feature extraction in hyperspectral images, Kernel-based target detection in hyperspectral images, Target and anomaly detection - hyperspectral imagery applications",

author = "Yanfeng Gu",

year = "2009",

month = nov,

day = "4",

doi = "10.1002/9780470748992.ch15",

language = "英语",

isbn = "9780470722114",

pages = "353--373",

booktitle = "Kernel Methods for Remote Sensing Data Analysis",

publisher = "John Wiley \& Sons, Ltd",

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T1 - KPCA Algorithm for Hyperspectral Target/Anomaly Detection

AU - Gu, Yanfeng

PY - 2009/11/4

Y1 - 2009/11/4

KW - Curve of average local singularity and sequence number of nonlinear principal components

KW - Hyperspectral images for numerical experiments

KW - Hyperspectral images in civilian and military fields

KW - KISD algorithm and processing flowchart

KW - KPCA algorithm for hyperspectral target/anomaly detection

KW - Kernel methods motivation for target and anomaly detection in hyperspectral images

KW - Kernel-based anomaly detection in hyperspectral images

KW - Kernel-based feature extraction in hyperspectral images

KW - Kernel-based target detection in hyperspectral images

KW - Target and anomaly detection - hyperspectral imagery applications

UR - https://www.scopus.com/pages/publications/84889407009

U2 - 10.1002/9780470748992.ch15

DO - 10.1002/9780470748992.ch15

M3 - 章节

AN - SCOPUS:84889407009

SN - 9780470722114

SP - 353

EP - 373

BT - Kernel Methods for Remote Sensing Data Analysis

PB - John Wiley & Sons, Ltd

ER -

KPCA Algorithm for Hyperspectral Target/Anomaly Detection

Keywords

Access to Document

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