Improved fractal-based methods for image compression

On the basis of the theory of iterated function systems (IFS), an image may be represented by a dynamic system, known as a fractal transformation, whose attractor is close to the image to be coded. For natural images, the parameters of such a dynamic system can usually be coded very compactly, which...

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Bibliographic Details
Main Author: Ruan, Yuxuan.
Other Authors: Toh, Guan Nge
Format: Thesis
Published: 2008
Subjects:
Online Access:http://hdl.handle.net/10356/3942
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author Ruan, Yuxuan.
author2 Toh, Guan Nge
author_facet Toh, Guan Nge
Ruan, Yuxuan.
author_sort Ruan, Yuxuan.
collection NTU
description On the basis of the theory of iterated function systems (IFS), an image may be represented by a dynamic system, known as a fractal transformation, whose attractor is close to the image to be coded. For natural images, the parameters of such a dynamic system can usually be coded very compactly, which makes this method suitable for image compression. In the fractal based compression methods, the problem of coding an image is to design such a dynamic system. To do this, an image is first partitioned into segments and each is approximated, in part, by another larger segment within the same image. These coding methods make use of the redundancies in the image at different scales. The decoding is then done by finding the attractor of the dynamic system and is typically an iterated process.
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spelling ntu-10356/39422023-07-04T15:45:00Z Improved fractal-based methods for image compression Ruan, Yuxuan. Toh, Guan Nge School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing On the basis of the theory of iterated function systems (IFS), an image may be represented by a dynamic system, known as a fractal transformation, whose attractor is close to the image to be coded. For natural images, the parameters of such a dynamic system can usually be coded very compactly, which makes this method suitable for image compression. In the fractal based compression methods, the problem of coding an image is to design such a dynamic system. To do this, an image is first partitioned into segments and each is approximated, in part, by another larger segment within the same image. These coding methods make use of the redundancies in the image at different scales. The decoding is then done by finding the attractor of the dynamic system and is typically an iterated process. Master of Engineering 2008-09-17T09:40:51Z 2008-09-17T09:40:51Z 2000 2000 Thesis http://hdl.handle.net/10356/3942 Nanyang Technological University application/pdf
spellingShingle DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing
Ruan, Yuxuan.
Improved fractal-based methods for image compression
title Improved fractal-based methods for image compression
title_full Improved fractal-based methods for image compression
title_fullStr Improved fractal-based methods for image compression
title_full_unstemmed Improved fractal-based methods for image compression
title_short Improved fractal-based methods for image compression
title_sort improved fractal based methods for image compression
topic DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing
url http://hdl.handle.net/10356/3942
work_keys_str_mv AT ruanyuxuan improvedfractalbasedmethodsforimagecompression