Satellite Image Restoration using the VMCA Model

One of the most common patterns of the geographic landscape is the fractal or nearfractal form. Unfortunately, most traditional methods of spatial interpolation assume some type of continuous and regionalizeable variation of the underlying geographic form, an assumption at odds with the observed fra...

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Detalles Bibliográficos
Autores principales: Anderson, Sharolyn, Fonstad, Mark Alan, Delrieux, Claudio
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2006
Materias:
Ciencias Informáticas
Satellite Image Restoration
Visual
VMCA Model
Graphics
Real time
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/20823
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-20823
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
Satellite Image Restoration
Visual
VMCA Model
Graphics
Real time
spellingShingle Ciencias Informáticas
Satellite Image Restoration
Visual
VMCA Model
Graphics
Real time
Anderson, Sharolyn
Fonstad, Mark Alan
Delrieux, Claudio
Satellite Image Restoration using the VMCA Model
topic_facet Ciencias Informáticas
Satellite Image Restoration
Visual
VMCA Model
Graphics
Real time
description One of the most common patterns of the geographic landscape is the fractal or nearfractal form. Unfortunately, most traditional methods of spatial interpolation assume some type of continuous and regionalizeable variation of the underlying geographic form, an assumption at odds with the observed fractal properties of many landscapes. An extremely simple iterative algorithm, the voter model cellular automata (CA), produces discontinuous fractal patterns useful for interpolation while at the same preserving a realistic amount of spatial autocorrelation, extracted from neighboring existing data, also found in these landscapes. This adaptive algorithm is based on the principle of iteratively interpolating a missing data point using the value of a randomly selected neighbor cell. The model can also be extended to interpolate field-like variables by adding random deviations from the randomly chosen neighbor cell value. In this paper we explore the effect of satellite image restoration using a simple VMCA over obscured by clouds areas. This model is computationally advantageous, given its localty and restricted underlying computational model. Thus, an adequate computer implementation may perform significantly faster than other restoration methods, with roughly similar overall results. Also the local/scalable/parallelizable nature of CAs allows hardware FPGA implementation that might be embedded within the imager devices in satellites and remote sensors. On the other end, a GPU implementation might take advantage of highly specialized parallel processors capablde of restoring huge images in real time.
format Objeto de conferencia
Objeto de conferencia
author Anderson, Sharolyn
Fonstad, Mark Alan
Delrieux, Claudio
author_facet Anderson, Sharolyn
Fonstad, Mark Alan
Delrieux, Claudio
author_sort Anderson, Sharolyn
title Satellite Image Restoration using the VMCA Model
title_short Satellite Image Restoration using the VMCA Model
title_full Satellite Image Restoration using the VMCA Model
title_fullStr Satellite Image Restoration using the VMCA Model
title_full_unstemmed Satellite Image Restoration using the VMCA Model
title_sort satellite image restoration using the vmca model
publishDate 2006
url http://sedici.unlp.edu.ar/handle/10915/20823
work_keys_str_mv AT andersonsharolyn satelliteimagerestorationusingthevmcamodel
AT fonstadmarkalan satelliteimagerestorationusingthevmcamodel
AT delrieuxclaudio satelliteimagerestorationusingthevmcamodel
bdutipo_str Repositorios
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