Processing of multiresolution thermal hyperspectral and digital color data: outcome of the 2014 IEEE GRSS data fusion contest

Wenzhi Liao; Xing Huang; Frieke Vancoillie; Sidharta Gautama; Aleksandra Pizurica; Wilfried Philips; Hui Liu; Tingting Zhu; Michal Shimoni; Gabriele Moser; Devis Tuia

doi:10.1109/JSTARS.2015.2420582

Processing of multiresolution thermal hyperspectral and digital color data: outcome of the 2014 IEEE GRSS data fusion contest

Wenzhi Liao, Xing Huang, Frieke Vancoillie, Sidharta Gautama, Aleksandra Pizurica, Wilfried Philips, Hui Liu, Tingting Zhu, Michal Shimoni, Gabriele Moser, Devis Tuia

Electronic And Electrical Engineering

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

207 Citations (Scopus)

Abstract

This paper reports the outcomes of the 2014 Data Fusion Contest organized by the Image Analysis and Data Fusion Technical Committee (IADF TC) of the IEEE Geoscience and Remote Sensing Society (IEEE GRSS). As for previous years, the IADF TC organized a data fusion contest aiming at fostering new ideas and solutions for multisource remote sensing studies. In the 2014 edition, participants considered multiresolution and multisensor fusion between optical data acquired at 20-cm resolution and long-wave (thermal) infrared hyperspectral data at 1-m resolution. The Contest was proposed as a double-track competition: one aiming at accurate landcover classification and the other seeking innovation in the fusion of thermal hyperspectral and color data. In this paper, the results obtained by the winners of both tracks are presented and discussed.

Original language	English
Pages (from-to)	2984-2996
Number of pages	13
Journal	IEEE Journal of Selected Topics in Earth Observation and Remote Sensing
Volume	8
Issue number	6
Early online date	15 May 2015
DOIs	https://doi.org/10.1109/JSTARS.2015.2420582
Publication status	Published - 30 Jun 2015

Keywords

multiresolution
multisource-data fusion
multimodal
landcover classification
thermal imaging
image analysis and data fusion (IADF)
hyperspectral
remote sensing
directional morphological profiles
supervised classification
surface temperature
domain adaptation
LiDAR data
resolution
extraction
features
polarization

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10.1109/JSTARS.2015.2420582

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Liao, W., Huang, X., Vancoillie, F., Gautama, S., Pizurica, A., Philips, W., Liu, H., Zhu, T., Shimoni, M., Moser, G., & Tuia, D. (2015). Processing of multiresolution thermal hyperspectral and digital color data: outcome of the 2014 IEEE GRSS data fusion contest. IEEE Journal of Selected Topics in Earth Observation and Remote Sensing, 8(6), 2984-2996. https://doi.org/10.1109/JSTARS.2015.2420582

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title = "Processing of multiresolution thermal hyperspectral and digital color data: outcome of the 2014 IEEE GRSS data fusion contest",

abstract = "This paper reports the outcomes of the 2014 Data Fusion Contest organized by the Image Analysis and Data Fusion Technical Committee (IADF TC) of the IEEE Geoscience and Remote Sensing Society (IEEE GRSS). As for previous years, the IADF TC organized a data fusion contest aiming at fostering new ideas and solutions for multisource remote sensing studies. In the 2014 edition, participants considered multiresolution and multisensor fusion between optical data acquired at 20-cm resolution and long-wave (thermal) infrared hyperspectral data at 1-m resolution. The Contest was proposed as a double-track competition: one aiming at accurate landcover classification and the other seeking innovation in the fusion of thermal hyperspectral and color data. In this paper, the results obtained by the winners of both tracks are presented and discussed.",

keywords = "multiresolution, multisource-data fusion, multimodal, landcover classification, thermal imaging, image analysis and data fusion (IADF), hyperspectral, remote sensing, directional morphological profiles, supervised classification, surface temperature, domain adaptation, LiDAR data, resolution, extraction, features, polarization",

author = "Wenzhi Liao and Xing Huang and Frieke Vancoillie and Sidharta Gautama and Aleksandra Pizurica and Wilfried Philips and Hui Liu and Tingting Zhu and Michal Shimoni and Gabriele Moser and Devis Tuia",

year = "2015",

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day = "30",

doi = "10.1109/JSTARS.2015.2420582",

language = "English",

volume = "8",

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journal = "IEEE Journal of Selected Topics in Earth Observation and Remote Sensing",

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Liao, W, Huang, X, Vancoillie, F, Gautama, S, Pizurica, A, Philips, W, Liu, H, Zhu, T, Shimoni, M, Moser, G & Tuia, D 2015, 'Processing of multiresolution thermal hyperspectral and digital color data: outcome of the 2014 IEEE GRSS data fusion contest', IEEE Journal of Selected Topics in Earth Observation and Remote Sensing, vol. 8, no. 6, pp. 2984-2996. https://doi.org/10.1109/JSTARS.2015.2420582

TY - JOUR

T1 - Processing of multiresolution thermal hyperspectral and digital color data

T2 - outcome of the 2014 IEEE GRSS data fusion contest

AU - Liao, Wenzhi

AU - Huang, Xing

AU - Vancoillie, Frieke

AU - Gautama, Sidharta

AU - Pizurica, Aleksandra

AU - Philips, Wilfried

AU - Liu, Hui

AU - Zhu, Tingting

AU - Shimoni, Michal

AU - Moser, Gabriele

AU - Tuia, Devis

PY - 2015/6/30

Y1 - 2015/6/30

N2 - This paper reports the outcomes of the 2014 Data Fusion Contest organized by the Image Analysis and Data Fusion Technical Committee (IADF TC) of the IEEE Geoscience and Remote Sensing Society (IEEE GRSS). As for previous years, the IADF TC organized a data fusion contest aiming at fostering new ideas and solutions for multisource remote sensing studies. In the 2014 edition, participants considered multiresolution and multisensor fusion between optical data acquired at 20-cm resolution and long-wave (thermal) infrared hyperspectral data at 1-m resolution. The Contest was proposed as a double-track competition: one aiming at accurate landcover classification and the other seeking innovation in the fusion of thermal hyperspectral and color data. In this paper, the results obtained by the winners of both tracks are presented and discussed.

AB - This paper reports the outcomes of the 2014 Data Fusion Contest organized by the Image Analysis and Data Fusion Technical Committee (IADF TC) of the IEEE Geoscience and Remote Sensing Society (IEEE GRSS). As for previous years, the IADF TC organized a data fusion contest aiming at fostering new ideas and solutions for multisource remote sensing studies. In the 2014 edition, participants considered multiresolution and multisensor fusion between optical data acquired at 20-cm resolution and long-wave (thermal) infrared hyperspectral data at 1-m resolution. The Contest was proposed as a double-track competition: one aiming at accurate landcover classification and the other seeking innovation in the fusion of thermal hyperspectral and color data. In this paper, the results obtained by the winners of both tracks are presented and discussed.

KW - multiresolution

KW - multisource-data fusion

KW - multimodal

KW - landcover classification

KW - thermal imaging

KW - image analysis and data fusion (IADF)

KW - hyperspectral

KW - remote sensing

KW - directional morphological profiles

KW - supervised classification

KW - surface temperature

KW - domain adaptation

KW - LiDAR data

KW - resolution

KW - extraction

KW - features

KW - polarization

UR - http://hdl.handle.net/1854/LU-5803396

U2 - 10.1109/JSTARS.2015.2420582

DO - 10.1109/JSTARS.2015.2420582

M3 - Article

SN - 1939-1404

VL - 8

SP - 2984

EP - 2996

JO - IEEE Journal of Selected Topics in Earth Observation and Remote Sensing

JF - IEEE Journal of Selected Topics in Earth Observation and Remote Sensing

IS - 6

ER -

Processing of multiresolution thermal hyperspectral and digital color data: outcome of the 2014 IEEE GRSS data fusion contest

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Keywords

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