Multi-Band Image Fusion Using Gaussian Process Regression with Sparse Rational Quadratic Kernel-Reference-Cited by-同舟云学术

Multi-Band Image Fusion Using Gaussian Process Regression with Sparse Rational Quadratic Kernel

Published:2019-07 Issue: Volume: Page:
ISSN:
Container-title:2019 22th International Conference on Information Fusion (FUSION)
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Author:

Longman Fodio S.¹,Mihaylova Lyudmila¹,Yang Le²,Topouzelis Konstantinos N.³

Affiliation:

1. University of Sheffield,Department of Automatic Control and System Engineering,Mappin Street,UK,S1 3JD

2. University of Canterbury,Department of Electrical and Computer Engineering,Chrischurch,New Zealand

3. University of the Aegean, University Hill,Department of Marine Sciences,Mytilene,Greece,81100

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8977236/9011156/09011352.pdf?arnumber=9011352

Reference20 articles.

1. S- and X-band SAR data fusion

2. Oil spill segmentation in fused Synthetic Aperture Radar images

3. image fusion using multi-decomposition levels of discrete wavelet transform;berbar;International Conference on Visual Information Engineering (VIE 2003) Ideas Applications Experience,2003

4. A Gaussian process regresion approach for fusion of remote sensing images for oil spill segmentation;longman;proceedings of 2018 21st International Conference on Information Fusion (FUSION),0

5. Online sparse multi-output gaussian process regression and learning;yang;IEEE Transactions on Signal and Information Processing over Networks,2018

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