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A Hierarchical ifs coding for Color Images

Electronics and Communications in Japan, Part III: Fundamental Electronic Science (English translation of Denshi Tsushin Gakkai Ronbunshi) 2000年第7期83卷 71-78页

作者： Nakano, Katsuhiko Nakagawa, Masahiro Faculty of Engineering Nagaoka University of Technology Nagaoka 940-2188 Japan

The hierarchical ifs coding proposed by the authors is applied to monochrome images. The present method is a fusion of the hierarchical procedure and fractal coding based on the iterated function system (ifs) theory. By using a hierarchical structure based on the Gaussian pyramid, the image is divided into frequency subbands so that the information is compressed. By using the information between the bands, the coding can effectively capture the similarity between the range and the domain. Further, an application of this method to color images is discussed. © 2000 Scripta Technica.

关键词： Hierarchical structure ifs coding Self-similarity YIQ color space

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A hierarchical ifs coding for color images

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ELECTRONICS AND COMMUNICATIONS IN JAPAN PART III-FUNDAMENTAL ELECTRONIC SCIENCE 2000年第7期83卷 71-78页

作者： Nakano, K Nakagawa, M Nagaoka Univ Technol Fac Engn Nagaoka Niigata 9402188 Japan

关键词： ifs coding hierarchical structure self-similarity YIQ color space

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Massively parallel processing approach to fractal image compression with near-optimal coefficient quantization

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JOURNAL OF SYSTEMS ARCHITECTURE 1999年第10期45卷 765-779页

作者： Palazzari, P Coli, M Lulli, G CR Casaccia ENEA HPCN Project I-00060 S Maria Di Galeria Italy Univ La Sapienza Dept Elect Engn I-00184 Rome Italy

In recent years Image Fractal Compression techniques (ifs) have gained more interest because of their capability to achieve high compression ratios while maintaining very good quality of the reconstructed image. The main drawback of such techniques is the very high computing time needed to determine the compressed code. In this work, after a brief description of ifs theory, we introduce the coefficient quantization problem, presenting two algorithms for its solution: the first one is based on Simulated Annealing while the second refers to a fast iterative algorithm. We discuss ifs parallel implementation at different level of granularity and we show that Massively Parallel Processing on SIMD machines is the best way to use all the large granularity parallelism offered by the problem. The results we present are achieved implementing the proposed algorithms for ifs compression and coefficient quantization on the MPP APE100/Quadrics machine. (C) 1999 Elsevier Science B.V. All rights reserved.

关键词： ifs coding simulated annealing quantization iterative optimization algorithm massively parallel processing

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