A comparison of different evolutive niching strategies for identifying a set of selfsimilar contractions for the IFS inverse problem

The key problem in fractal image compression is that of obtaining the IFS code (a set of linear transformations)which approximates a given image with a certain prescribed accuracy (inverse IFS problem).In this paper,we analyze and compare the performance of sharing and crowding niching techniques fo...

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Autores principales: Gutiérrez Llorente, José Manuel, Ivanissevich, María Laura, Cofiño, Antonio S.
Formato: Articulo
Lenguaje:Inglés
Publicado: 2001
Materias:
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/9417
http://journal.info.unlp.edu.ar/wp-content/uploads/p3.pdf
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id I19-R120-10915-9417
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
iterated function systems
image compression
Fractals
Algorithms
spellingShingle Ciencias Informáticas
iterated function systems
image compression
Fractals
Algorithms
Gutiérrez Llorente, José Manuel
Ivanissevich, María Laura
Cofiño, Antonio S.
A comparison of different evolutive niching strategies for identifying a set of selfsimilar contractions for the IFS inverse problem
topic_facet Ciencias Informáticas
iterated function systems
image compression
Fractals
Algorithms
description The key problem in fractal image compression is that of obtaining the IFS code (a set of linear transformations)which approximates a given image with a certain prescribed accuracy (inverse IFS problem).In this paper,we analyze and compare the performance of sharing and crowding niching techniques for identifying optimal selfsimilar transformations likely to represent a selfsimilar area within the image. The best results are found using the deterministic crowding method.We also present an nteractive Matlab program implementing the algorithms described in the paper.The key problem in fractal image compression is that of obtaining the IFS code (a set of linear transformations)which approximates a given image with a certain prescribed accuracy (inverse IFS problem).In this paper,we analyze and compare the performance of sharing and crowding niching techniques for identifying optimal selfsimilar transformations likely to represent a selfsimilar area within the image. The best results are found using the deterministic crowding method.We also present an nteractive Matlab program implementing the algorithms described in the paper.
format Articulo
Articulo
author Gutiérrez Llorente, José Manuel
Ivanissevich, María Laura
Cofiño, Antonio S.
author_facet Gutiérrez Llorente, José Manuel
Ivanissevich, María Laura
Cofiño, Antonio S.
author_sort Gutiérrez Llorente, José Manuel
title A comparison of different evolutive niching strategies for identifying a set of selfsimilar contractions for the IFS inverse problem
title_short A comparison of different evolutive niching strategies for identifying a set of selfsimilar contractions for the IFS inverse problem
title_full A comparison of different evolutive niching strategies for identifying a set of selfsimilar contractions for the IFS inverse problem
title_fullStr A comparison of different evolutive niching strategies for identifying a set of selfsimilar contractions for the IFS inverse problem
title_full_unstemmed A comparison of different evolutive niching strategies for identifying a set of selfsimilar contractions for the IFS inverse problem
title_sort comparison of different evolutive niching strategies for identifying a set of selfsimilar contractions for the ifs inverse problem
publishDate 2001
url http://sedici.unlp.edu.ar/handle/10915/9417
http://journal.info.unlp.edu.ar/wp-content/uploads/p3.pdf
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