Processing of Multiresolution Thermal Hyperspectral and Digital Color Data: Outcome of the 2014 IEEE GRSS Data Fusion Contest

Wenzhi Liao; Xin Huang; Frieke Van Coillie; Sidharta Gautama; Aleksandra Pižurica; 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
, Xin Huang
, Frieke Van Coillie
, Sidharta Gautama
, Aleksandra Pižurica
, Wilfried Philips
, Hui Liu
, Tingting Zhu
, Michal Shimoni
, Gabriele Moser
, Devis Tuia

University of Ghent
Wuhan University
University of Genoa
University of Zurich

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

225 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
Article number	7109121
Pages (from-to)	2984-2996
Number of pages	13
Journal	IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Volume	8
Issue number	6
DOIs	https://doi.org/10.1109/JSTARS.2015.2420582
Publication status	Published - 1 Jun 2015

Keywords

Hyperspectral
image analysis and data fusion (IADF)
landcover classification
multimodal-
multiresolution-
multisource-data fusion
thermal imaging

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10.1109/JSTARS.2015.2420582

Cite this

Liao, W., Huang, X., Van Coillie, F., Gautama, S., Pižurica, 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 Applied Earth Observations and Remote Sensing, 8(6), 2984-2996. Article 7109121. 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 = "Hyperspectral, image analysis and data fusion (IADF), landcover classification, multimodal-, multiresolution-, multisource-data fusion, thermal imaging",

author = "Wenzhi Liao and Xin Huang and \{Van Coillie\}, Frieke and Sidharta Gautama and Aleksandra Pi{\v z}urica and Wilfried Philips and Hui Liu and Tingting Zhu and Michal Shimoni and Gabriele Moser and Devis Tuia",

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year = "2015",

month = jun,

day = "1",

doi = "10.1109/JSTARS.2015.2420582",

language = "English",

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Liao, W, Huang, X, Van Coillie, F, Gautama, S, Pižurica, 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 Applied Earth Observations and Remote Sensing, vol. 8, no. 6, 7109121, pp. 2984-2996. https://doi.org/10.1109/JSTARS.2015.2420582

Processing of Multiresolution Thermal Hyperspectral and Digital Color Data: Outcome of the 2014 IEEE GRSS Data Fusion Contest. / Liao, Wenzhi; Huang, Xin; Van Coillie, Frieke et al.
In: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol. 8, No. 6, 7109121, 01.06.2015, p. 2984-2996.

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

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, Xin

AU - Van Coillie, Frieke

AU - Gautama, Sidharta

AU - Pižurica, Aleksandra

AU - Philips, Wilfried

AU - Liu, Hui

AU - Zhu, Tingting

AU - Shimoni, Michal

AU - Moser, Gabriele

AU - Tuia, Devis

PY - 2015/6/1

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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 - Hyperspectral

KW - image analysis and data fusion (IADF)

KW - landcover classification

KW - multimodal-

KW - multiresolution-

KW - multisource-data fusion

KW - thermal imaging

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

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

IS - 6

M1 - 7109121

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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