### fiasco-1.3 README file

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    	 FIASCO («F»ractal «I»mage «A»nd «S»equence «CO»dec)
    		       Copyright (C) 1994-2000
         Ullrich Hafner <hafner@bigfoot.de>, http://ulli.linuxave.net
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    FIASCO is an image and video compression system based on fractal
    coding which outperforms the well known JPEG and MPEG
    standards. FIASCO has been developed during my Ph.D. thesis "Low
    Bit-Rate Image and Video Coding with Weighted Finite Automata", Mensch
    & Buch Verlag, ISBN 3-89820-002-7.

    FIASCO consists of the following components:

    afiasco
    	An X11 application to analyse and visualize a compressed image,
            see separate manual page afiasco(1) for details.

    bfiasco
    	A tool to generate the binary tree of the compressed image,
            see separate manual page bfiasco(1) for details.

    cfiasco
    	Command line application to compress images and videos, see
            separate manual page cfiasco(1) for details. (File extension for
            FIASCO files: .fco)

    dfiasco
    	An X11 application to decompress and display images and videos,
            see separate manual page dfiasco(1) for details.

    efiasco
    	A tool to edit and concatenate several FIASCO streams,
            see separate manual page efiasco(1) for details.

    libfiasco.so
    fiasco.h
    	A compression library to provide compression and decompression
    	of FIASCO files for other applications, see separate README
    	file doc/README.LIB or manual pages fiasco_coder(3),
    	fiasco_decoder(3) for details.

    gimpplugin
    	A plugin for GIMP 1.1.x to read FIASCO images and movies

    FIASCO is free software; you can redistribute it and/or modify it
    under the terms of the GNU General Public License as published by the
    Free Software Foundation; either version 2 of the License, or (at your
    option) any later version.

    FIASCO is distributed in the hope that it will be useful, but WITHOUT
    ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
    FITNESS FOR A PARTICULAR PURPOSE.  See the GNU General Public License
    for more details.

    You should have received a copy of the GNU General Public License
    along with FIASCO; if not, write to the Free Software Foundation,
    Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA

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      Low Bit-Rate Image and Video Coding with Weighted Finite Automata

    			       ABSTRACT
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    Recently, the need for efficient image compression systems can be
    seen, e.g., in the rapidly growing field of world wide web
    applications: not only still pictures but also small video sequences
    are used to enhance the design of private and commercial web pages.
    However, the speed of most internet connections is very limited, so
    the amount of data to be transmitted must be dramatically reduced in
    order to give a practical solution.

    Weighted Finite Automata (WFA) exploit self-similarities within single
    pictures and also sequences of pictures to remove spatial, spectral
    and temporal redundancies. Their implementation combines techniques
    from hierarchical methods related to quadtrees, vector-quantization,
    matching pursuit, and fractal coding.

    This thesis discusses important modifications of the original WFA
    codec introduced by Culik and Kari which, in total, increase the
    compression performance for low bit-rates to be on a par with
    state-of-the-art codecs like embedded zerotree wavelet coding for
    still images or H.263+ for video streams.

    A crucial aspect during the development of our codec was the
    performance of the matching pursuit algorithm used to generate an
    approximation of the sub-images: we must carefully choose the set of
    dictionary vectors as well as the quantization parameters of the
    approximation coefficients. Last but not least, all coefficients and
    indices must be efficiently stored using specially tuned models.

    Not as crucial as the latter aspect but still important is the degree
    of nondeterminism used by a WFA. We show that without nondeterminism
    the approximation quality will quickly degenerate, but, on the other
    hand, only a very restricted usage of nondeterminism can be stored
    efficiently.

    Finally, the application to video coding is investigated in detail.
    We show that due to their simple mathematical structure, WFA provide
    an ideal platform for efficient hybrid compression methods. So we
    combined a hierarchical block based motion-compensation with the still
    picture coder to form an efficient video codec. After all, we
    optimized the run-time of the WFA video decoder to provide real-time
    software decoding on most personal computer platforms.

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