Image-model coupling: a simple information theoretic perspective for image sequences

Images are widely used to visualise physical processes. Models may be developed which attempt to replicate those processes and their effects. The technique of coupling model output to images, which is here called "image-model coupling", may be used to help understand the underlying...

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Main Authors: N. D. Smith, C. N. Mitchell, C. J. Budd
Format: Article
Language:English
Published: Copernicus Publications 2009-03-01
Series:Nonlinear Processes in Geophysics
Online Access:http://www.nonlin-processes-geophys.net/16/197/2009/npg-16-197-2009.pdf
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spelling doaj-fa3b4d1526f74ed79f1342dd779ec0912020-11-25T01:19:13ZengCopernicus PublicationsNonlinear Processes in Geophysics1023-58091607-79462009-03-01162197210Image-model coupling: a simple information theoretic perspective for image sequencesN. D. SmithC. N. MitchellC. J. BuddImages are widely used to visualise physical processes. Models may be developed which attempt to replicate those processes and their effects. The technique of coupling model output to images, which is here called "image-model coupling", may be used to help understand the underlying physical processes, and better understand the limitations of the models. An information theoretic framework is presented for image-model coupling in the context of communication along a discrete channel. The physical process may be regarded as a transmitter of images and the model as part of a receiver which decodes or recognises those images. Image-model coupling may therefore be interpreted as image recognition. Of interest are physical processes which exhibit "memory". The response of such a system is not only dependent on the current values of driver variables, but also on the recent history of drivers and/or system description. Examples of such systems in geophysics include the ionosphere and Earth's climate. The discrete channel model is used to help derive expressions for matching images and model output, and help analyse the coupling. http://www.nonlin-processes-geophys.net/16/197/2009/npg-16-197-2009.pdf
collection DOAJ
language English
format Article
sources DOAJ
author N. D. Smith
C. N. Mitchell
C. J. Budd
spellingShingle N. D. Smith
C. N. Mitchell
C. J. Budd
Image-model coupling: a simple information theoretic perspective for image sequences
Nonlinear Processes in Geophysics
author_facet N. D. Smith
C. N. Mitchell
C. J. Budd
author_sort N. D. Smith
title Image-model coupling: a simple information theoretic perspective for image sequences
title_short Image-model coupling: a simple information theoretic perspective for image sequences
title_full Image-model coupling: a simple information theoretic perspective for image sequences
title_fullStr Image-model coupling: a simple information theoretic perspective for image sequences
title_full_unstemmed Image-model coupling: a simple information theoretic perspective for image sequences
title_sort image-model coupling: a simple information theoretic perspective for image sequences
publisher Copernicus Publications
series Nonlinear Processes in Geophysics
issn 1023-5809
1607-7946
publishDate 2009-03-01
description Images are widely used to visualise physical processes. Models may be developed which attempt to replicate those processes and their effects. The technique of coupling model output to images, which is here called "image-model coupling", may be used to help understand the underlying physical processes, and better understand the limitations of the models. An information theoretic framework is presented for image-model coupling in the context of communication along a discrete channel. The physical process may be regarded as a transmitter of images and the model as part of a receiver which decodes or recognises those images. Image-model coupling may therefore be interpreted as image recognition. Of interest are physical processes which exhibit "memory". The response of such a system is not only dependent on the current values of driver variables, but also on the recent history of drivers and/or system description. Examples of such systems in geophysics include the ionosphere and Earth's climate. The discrete channel model is used to help derive expressions for matching images and model output, and help analyse the coupling.
url http://www.nonlin-processes-geophys.net/16/197/2009/npg-16-197-2009.pdf
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