This package contains MatLab code for analyzing and synthesizing
digital image of visual texture. The algorithm is described in the
references given at the bottom of this document. Further information,
as well the most recent versions of the code, are available at
http://www.cns.nyu.edu/~lcv/texture/
Incremental changes to the code are documented in the ChangeLog file.
Written by Javier Portilla and Eero Simoncelli, 1999-2000.
Comments/Suggestions/Bugs to:
javier@decsai.ugr.es
eero.simoncelli@nyu.edu
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INSTALLATION
1) download and unpack the code. You can put the code anywhere on
your system, but we'll assume it's in a directory named "textureSynth".
2) download and unpack the matlabPyrTools package from
https://github.com/LabForComputationalVision/matlabPyrTools
This is a collection of tools for multi-scale decomposition of
images. You can put the code anywhere on your system, but we'll
assume it's in a directory named "matlabPyrTools". Please use version
1.4 or newer of the matlabPyrTools.
3) Run matlab, and put the matlabPyrTools directory in your path:
> path('matlabPyrTools', path);
4) The matlabPyrTools distribution includes a MEX subdirectory containing
binary executables, precompiled for various platforms (SunOS,Solaris,
Linux,Windows). You may need to recompile these on your platform. In
addition, you should either move the relavent files from the MEX
subdirectory into the main directory, OR create a link/alias to them,
OR place the MEX subdirectory in your matlab path.
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USING THE SOFTWARE
- To see a demonstration, start Matlab, change directories (using
"cd") into the textureSynth directory, and execute "example1"
(without the quotations).
- If you want to learn how to use the texture analysis and synthesis
functions, take a look at example1.m and example2.m (these include
many explanatory comments).
- For a listing of matlab function included in this package, execute
"help textureSynth"
- For details on any of the functions, execute "help <name_of_function>"
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REFERENCES
J Portilla and E P Simoncelli. A Parametric Texture Model based on
Joint Statistics of Complex Wavelet Coefficients. Int'l Journal
of Computer Vision. 40(1):49-71, October, 2000.
http://www.cns.nyu.edu/~eero/ABSTRACTS/portilla99-abstract.html
J Portilla and E P Simoncelli Texture Modeling and Synthesis using
Joint Statistics of Complex Wavelet Coefficients. IEEE Workshop
on Statistical and Computational Theories of Vision, Fort
Collins, CO, 22 June 1999.
http://www.cns.nyu.edu/~eero/ABSTRACTS/portilla99a-abstract.html
J Portilla and E P Simoncelli. Texture Representation and Synthesis
Using Correlation of Complex Wavelet Coefficient
Magnitudes. Technical Report #54, Consejo Superior de
Investigaciones Cientificas (CSIC), Madrid. 29 March 1999.
http://www.cns.nyu.edu/~eero/ABSTRACTS/portilla98-abstract.html
E P Simoncelli and J Portilla. Texture Characterization via Joint
Statistics of Wavelet Coefficient Magnitudes. In 5th IEEE Int'l
Conf on Image Processing. Chicago, IL. Oct 4-7, 1998.
http://www.cns.nyu.edu/~eero/ABSTRACTS/simoncelli98b-abstract.html