Advances in Hyperspectral Image and Signal Processing A comprehensive overview of the state of the art

被引：679

作者：

Ghamisi, Pedram ^{[1
,2
]}

Yokoya, Naoto ^{[3
]}

Li, Jun ^{[4
]}

Liao, Wenzhi ^{[5
]}

Liu, Sicong ^{[6
]}

Plaza, Javier ^{[7
]}

Rasti, Behnood ^{[8
,9
]}

Plaza, Antonio ^{[7
]}

机构：

[1] German Aerosp Ctr, Remote Sensing Technol Inst, Munich, Germany

[2] Tech Univ Munich, Signal Proc Earth Observat, Munich, Germany

[3] Univ Tokyo, Dept Adv Interdisciplinary Studies, Tokyo, Japan

[4] Sun Yat Sen Univ, Guangdong Prov Key Lab Urbanizat & Geosimulat, Ctr Integrated Geog Informat Anal, Sch Geog & Planning, Guangzhou, Guangdong, Peoples R China

[5] Univ Ghent, Dept Telecommun & Informat Proc, Ghent, Belgium

[6] Tongji Univ, Coll Surveying & Geoinformat, Shanghai, Peoples R China

[7] Univ Extremadura, Dept Technol Comp & Commun, Badajoz, Spain

[8] Keilir Inst Technol, Reykjanesbaer, Iceland

[9] Univ Iceland, Dept Elect & Comp Engn, Reykjavik, Iceland

来源：

IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE | 2017年 / 5卷 / 04期

关键词：

SPECTRAL-SPATIAL CLASSIFICATION; WEIGHTED FEATURE-EXTRACTION; EXTREME-LEARNING-MACHINE; SUPPORT VECTOR MACHINES; REMOTE-SENSING IMAGES; FEATURE-SELECTION; DIMENSIONALITY REDUCTION; ATTRIBUTE PROFILES; NEURAL-NETWORK; ENDMEMBER IDENTIFICATION;

D O I：

10.1109/MGRS.2017.2762087

中图分类号：

P3 [地球物理学]; P59 [地球化学];

学科分类号：

0708 ; 070902 ;

摘要：

Recent advances in airborne and spaceborne hyperspectral imaging technology have provided end users with rich spectral, spatial, and temporal information. They have made a plethora of applications feasible for the analysis of large areas of the Earth?s surface. However, a significant number of factors-such as the high dimensions and size of the hyperspectral data, the lack of training samples, mixed pixels, light-scattering mechanisms in the acquisition process, and different atmospheric and geometric distortions-make such data inherently nonlinear and complex, which poses major challenges for existing methodologies to effectively process and analyze the data sets. Hence, rigorous and innovative methodologies are required for hyperspectral image (HSI) and signal processing and have become a center of attention for researchers worldwide. © 2013 IEEE.

引用

页码：37 / 78

页数：42

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