|Fractal image compression
|Awarded by Multi-disciplinary Studies, HKPU
|Image processing -- Digital techniques
Hong Kong Polytechnic University -- Dissertations
|61 leaves : ill. ; 30 cm
|Being influenced by technological advances in computer technology, research in image compression has become increasingly important. Powerful microprocessor chips roll out quickly as compared with a decade ago. Multi-media becomes available and affordable for home users. CD-ROM and display equipment become more and more sophisticated. Users are no longer satisfied with the image retrieve speed and huge storage space requirement. The application of fractal theory to the compression of image data has drawn much attention. This is because of its potential to achieve a greater compression ratio than standard methods. Transform coding is usually applied to a quantized image to perform image compression. The Discrete Cosine Transform (DCT) is one such method and is adopted by the Joint Photographic Experts Group (JPEG) as the standard for the compression of image data. This method may not provide enough compression to make digital images practical for many applications. This gives rise to the interest in exploration of the application of fractal theory to image compression. Fractal theory and hence the concept of Iterated Function System (IFS) will be introduced. The generation of fractal images by IFS codes will be explained in detail. Classical IFS and characteristic of IFS will be discussed and illustrated. IFS theory is then applied to the problem of image compression. There are two methods, based on IFS, to compress image data. One is the Collage Theorem and the other is the Distribution Moments method. They are used to find an IFS which provides a close approximation of the original image. An experimental approach is employed where two programs were developed based on IFS approach to testify and verify the theory. The encoding algorithm and procedures are explained in details. However, this implementation is far from satisfactory. It only served as a starting point to explore into the world of fractal image generation.
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