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Image fusion by spatially adaptive filtering using downscaling cokriging

Image fusion by spatially adaptive filtering using downscaling cokriging
Image fusion by spatially adaptive filtering using downscaling cokriging
The aim of this paper was to extend the method of downscaling cokriging for image fusion by making the method spatially adaptive in that the filter parameters (cokriging weights) can change across the image. The method can adapt itself to the usual statistical non-homogeneity (spatially variable mean, variance and correlation length) of a satellite sensor image that covers an area with different spatial patterns of geographical objects or different terrain types. The solution adopted was to estimate the models of covariances and cross-covariances (or semivariograms and cross-semivariograms) by the same procedure as described in Pardo-Iguzquiza et al. (2006) but with the method applied locally instead of globally. The correct implementation of this local estimation is the key for computational feasibility and prediction efficiency. Two parameters to be taken into account are the grid of locations on which a moving window is centred (local modelling is performed inside this window) and the size of this moving window. With respect to the latter parameter, there is a trade-off between a size small enough to make the procedure locally adaptive and large enough to produce reliable statistical estimates. The computational burden will impose limits to the distance between grid points on which the local moving window is centred. A case study with Landsat ETM+ images was used to show the implementation of the method and the result was evaluated using several statistics widely used for assessing the quality of a fused image, apart from its visual appearance.
0924-2716
337-346
Pardo-Iguzquiza, E.
a7c2ba6d-d6b1-4005-9cea-188357c26e8a
Rodriguez-Galiano, V.F.
1eb6a1dd-f73d-4e90-a9cf-a51f20712c3c
Chico-Olmo, M.
60fb2ddb-159a-4e0f-8a50-2931c6c4c2aa
Atkinson, P.M.
96e96579-56fe-424d-a21c-17b6eed13b0b
Pardo-Iguzquiza, E.
a7c2ba6d-d6b1-4005-9cea-188357c26e8a
Rodriguez-Galiano, V.F.
1eb6a1dd-f73d-4e90-a9cf-a51f20712c3c
Chico-Olmo, M.
60fb2ddb-159a-4e0f-8a50-2931c6c4c2aa
Atkinson, P.M.
96e96579-56fe-424d-a21c-17b6eed13b0b

Pardo-Iguzquiza, E., Rodriguez-Galiano, V.F., Chico-Olmo, M. and Atkinson, P.M. (2011) Image fusion by spatially adaptive filtering using downscaling cokriging. ISPRS Journal of Photogrammetry and Remote Sensing, 66 (3), 337-346. (doi:10.1016/j.isprsjprs.2011.01.001).

Record type: Article

Abstract

The aim of this paper was to extend the method of downscaling cokriging for image fusion by making the method spatially adaptive in that the filter parameters (cokriging weights) can change across the image. The method can adapt itself to the usual statistical non-homogeneity (spatially variable mean, variance and correlation length) of a satellite sensor image that covers an area with different spatial patterns of geographical objects or different terrain types. The solution adopted was to estimate the models of covariances and cross-covariances (or semivariograms and cross-semivariograms) by the same procedure as described in Pardo-Iguzquiza et al. (2006) but with the method applied locally instead of globally. The correct implementation of this local estimation is the key for computational feasibility and prediction efficiency. Two parameters to be taken into account are the grid of locations on which a moving window is centred (local modelling is performed inside this window) and the size of this moving window. With respect to the latter parameter, there is a trade-off between a size small enough to make the procedure locally adaptive and large enough to produce reliable statistical estimates. The computational burden will impose limits to the distance between grid points on which the local moving window is centred. A case study with Landsat ETM+ images was used to show the implementation of the method and the result was evaluated using several statistics widely used for assessing the quality of a fused image, apart from its visual appearance.

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More information

Published date: May 2011
Organisations: Global Env Change & Earth Observation

Identifiers

Local EPrints ID: 343287
URI: http://eprints.soton.ac.uk/id/eprint/343287
ISSN: 0924-2716
PURE UUID: ba62c9e1-a82f-43c4-9bf8-ce3c9ca0194c
ORCID for P.M. Atkinson: ORCID iD orcid.org/0000-0002-5489-6880

Catalogue record

Date deposited: 02 Oct 2012 16:32
Last modified: 15 Mar 2024 02:47

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Contributors

Author: E. Pardo-Iguzquiza
Author: V.F. Rodriguez-Galiano
Author: M. Chico-Olmo
Author: P.M. Atkinson ORCID iD

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