Performance Analysis of Iteration-free Fractal Image Coding: Using Vector Quantization, Genetic Algorithm and Simulated Annealing Techniques - Couverture souple

Kamal, Nadira Banu

 
9783659164484: Performance Analysis of Iteration-free Fractal Image Coding: Using Vector Quantization, Genetic Algorithm and Simulated Annealing Techniques
Couverture souple
ISBN 10 : 3659164488 ISBN 13 : 9783659164484
Editeur : LAP LAMBERT Academic Publishing, 2012

Synopsis

In fractal image compression the encoding step is computationally expensive. A large number of sequential searches through a list of domain from the domain pool are carried out while trying to find the best matches for image portions called ranges. Vector Quantization using Linde Buzo Gray algorithm helps in reducing the redundant domain blocks. The mean image constructed using the range blocks was used as the domain pool for the construction of the synthetic codebook. In order to reduce the time consumption the mean, edge strength and texture feature of each range block are determined and compared with the domains in the codebook in order to reduce the redundant domain blocks for each range block. Genetic Algorithm (GA) and Simulated Annealing (SA) are optimization techniques, hence it is proposed to use GA and SA for finding the best match of the domain block to the range block. It is observed that the proposed technique using GA achieves excellent performance in image quality and SA with reduction in computation time. The performance analysis of all the three proposed techniques in iteration-free fractal image compression is reported and discussed in detail in this book.

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Présentation de l'éditeur

In fractal image compression the encoding step is computationally expensive. A large number of sequential searches through a list of domain from the domain pool are carried out while trying to find the best matches for image portions called ranges. Vector Quantization using Linde Buzo Gray algorithm helps in reducing the redundant domain blocks. The mean image constructed using the range blocks was used as the domain pool for the construction of the synthetic codebook. In order to reduce the time consumption the mean, edge strength and texture feature of each range block are determined and compared with the domains in the codebook in order to reduce the redundant domain blocks for each range block. Genetic Algorithm (GA) and Simulated Annealing (SA) are optimization techniques, hence it is proposed to use GA and SA for finding the best match of the domain block to the range block. It is observed that the proposed technique using GA achieves excellent performance in image quality and SA with reduction in computation time. The performance analysis of all the three proposed techniques in iteration-free fractal image compression is reported and discussed in detail in this book.

Biographie de l'auteur

I am a Professor in the Department of Computer Science of TBAK College for Women, India since 1988. I did my MSc in Anna University and PhD in Manonmanium Sundaranar University. My area of research includes Digital Image Processing and Soft Computing. I am an editor of a few International Journals and Conferences and published more than 20 papers.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
LAP LAMBERT Academic Publishing
Date d'édition
2012
Langue
anglais
ISBN 10 
3659164488
ISBN 13 
9783659164484
Reliure
Broché
Nombre de pages
128
Coordonnées du fabricant
non disponible
Personne responsable
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