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

Nadira Banu Kamal

ISBN 10: 3659164488 / ISBN 13: 9783659164484

Published by LAP Lambert Academic Publishing, 2012

About this Item

Performance Analysis of Iteration-free Fractal Image Coding | Using Vector Quantization, Genetic Algorithm and Simulated Annealing Techniques | Nadira Banu Kamal | Taschenbuch | Englisch | LAP Lambert Academic Publishing | EAN 9783659164484 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Seller Inventory # 106329356

Bibliographic Details

• Title: Performance Analysis of Iteration-free Fractal Image Coding | Using Vector Quantization, Genetic Algorithm and Simulated Annealing Techniques
• Publisher: LAP Lambert Academic Publishing
• Publication Date: 2012
• Language: English
• ISBN 10: 3659164488
• ISBN 13: 9783659164484
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 150W x 7H x 219D millimeters 150 millimeters width by 7 millimeters height by 219 millimeters depth
• Weight: 240 grams
• Seller catalogs:
  • Bücher

About this title

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.

About the Author

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.