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Combining Fractal Coding and Orthogonal Linear Transforms
Author(s) -
Michele Nappi,
Daniel Riccio
Publication year - 2011
Publication title -
isrn signal processing
Language(s) - English
Resource type - Journals
eISSN - 2090-505X
pISSN - 2090-5041
DOI - 10.5402/2011/359592
Subject(s) - embedding , fractal , coding (social sciences) , computer science , fractal compression , algorithm , image compression , pattern recognition (psychology) , image processing , artificial intelligence , search engine indexing , data compression , segmentation , mathematics , computer vision , theoretical computer science , image (mathematics) , mathematical analysis , statistics
Many desirable properties make fractals a powerful mathematic model applied in several image processing and pattern recognition tasks: image coding, segmentation, feature extraction, and indexing, just to cite some of them. Unfortunately, they are based on a strong asymmetric scheme, consequently suffering from very high coding times. On the other side, linear transforms are quite time balanced, allowing them to be usefully exploited in realtime applications, but they do not provide comparable performances with respect to the image quality for high bit rates. In this paper, we investigate different levels of embedding orthogonal linear transforms in the fractal coding scheme. Experimental results show a clear improved quality for compression ratios up to 15 : 1

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