Advances in hyperspectral image and signal processing: a comprehensive overview of the state of the art

Pedram Ghamisi, Naoto Yokoya, Jun Li, Wenzhi Liao, Sicong Liu, Javier Plaza, Behnood Rasti, Antonio Plaza

Research output: Contribution to journalArticle

63 Citations (Scopus)

Abstract

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.
LanguageEnglish
Pages37-78
Number of pages42
JournalIEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE
Volume5
Issue number4
DOIs
Publication statusPublished - 31 Dec 2017

Fingerprint

signal processing
image processing
methodology
light scattering
acquisition
pixel
education
pixels
state of the art
analysis

Keywords

  • hyperspectral Imaging
  • signal processing
  • feature extraction
  • image restoration
  • spatial resolution
  • algorithm design and analysis
  • data preprocessing
  • data analysis
  • geophysical image processing
  • remote sensing

Cite this

Ghamisi, Pedram ; Yokoya, Naoto ; Li, Jun ; Liao, Wenzhi ; Liu, Sicong ; Plaza, Javier ; Rasti, Behnood ; Plaza, Antonio. / Advances in hyperspectral image and signal processing : a comprehensive overview of the state of the art. 2017 ; Vol. 5, No. 4. pp. 37-78.
@article{a4bcde3ea2ae43cb9817770f40802ce3,
title = "Advances in hyperspectral image and signal processing: a comprehensive overview of the state of the art",
abstract = "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.",
keywords = "hyperspectral Imaging, signal processing, feature extraction, image restoration, spatial resolution, algorithm design and analysis, data preprocessing, data analysis, geophysical image processing, remote sensing",
author = "Pedram Ghamisi and Naoto Yokoya and Jun Li and Wenzhi Liao and Sicong Liu and Javier Plaza and Behnood Rasti and Antonio Plaza",
year = "2017",
month = "12",
day = "31",
doi = "10.1109/MGRS.2017.2762087",
language = "English",
volume = "5",
pages = "37--78",
number = "4",

}

Ghamisi, P, Yokoya, N, Li, J, Liao, W, Liu, S, Plaza, J, Rasti, B & Plaza, A 2017, 'Advances in hyperspectral image and signal processing: a comprehensive overview of the state of the art' vol. 5, no. 4, pp. 37-78. https://doi.org/10.1109/MGRS.2017.2762087

Advances in hyperspectral image and signal processing : a comprehensive overview of the state of the art. / Ghamisi, Pedram; Yokoya, Naoto; Li, Jun; Liao, Wenzhi; Liu, Sicong; Plaza, Javier; Rasti, Behnood; Plaza, Antonio.

Vol. 5, No. 4, 31.12.2017, p. 37-78.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Advances in hyperspectral image and signal processing

T2 - a comprehensive overview of the state of the art

AU - Ghamisi, Pedram

AU - Yokoya, Naoto

AU - Li, Jun

AU - Liao, Wenzhi

AU - Liu, Sicong

AU - Plaza, Javier

AU - Rasti, Behnood

AU - Plaza, Antonio

PY - 2017/12/31

Y1 - 2017/12/31

N2 - 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.

AB - 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.

KW - hyperspectral Imaging

KW - signal processing

KW - feature extraction

KW - image restoration

KW - spatial resolution

KW - algorithm design and analysis

KW - data preprocessing

KW - data analysis

KW - geophysical image processing

KW - remote sensing

UR - http://hdl.handle.net/1854/LU-8553067

U2 - 10.1109/MGRS.2017.2762087

DO - 10.1109/MGRS.2017.2762087

M3 - Article

VL - 5

SP - 37

EP - 78

IS - 4

ER -