Contact: Alireza Golestaneh ([email protected]) and Lina Karam ([email protected]) 
 Image, Video, and Usabilty (IVU) Lab, Arizona State University

Abstract:

Natural and artificial textures occur frequently in images and in video sequences. Image/video coding systems based on texture synthesis can make use of a reliable texture synthesis quality assessment method in order to improve the compression performance in terms of perceived quality and bit-rate. 
Existing objective visual quality assessment methods do not perform satisfactorily when predicting the synthesized texture quality. 
In this dataset we show the effect of texture granularity, on the quality of synthesized textures. For this purpose, subjective studies are conducted to assess the quality of synthesized textures with different levels (low, medium, high) of perceived texture granularity using different types of texture synthesis methods.

 Database:

To evaluate the effect of granularity on synthesized textures we have selected 21 reference textures  consists of textures with low, medium and high granularity levels.
In Figure 1, examples for low, medium and high granularity textures is shown.
A low granularity texture will have large primitives (objects) as compared to medium and high granularity textures.
For high granularity textures the primitive sizes are very small. 

Subjective Testing:

A subjective study was conducted on 105 synthesized textures generated using 5 texture synthesis algorithms (See Ref [1] for details), which span the parametric, non-parametric, statistical,  and non-statistical methods. Since not all the algorithms support the synthesis of color images, the grayscale images were used in these experiments. 

Citation: 

If you plan to use the database, please cite the following paper:

@inproceedings{golestaneh2015effect,
 title={The effect of texture granularity on texture synthesis quality},
 author={Golestaneh, S Alireza and Subedar, Mahesh M and Karam, Lina J},
 booktitle={Applications of Digital Image Processing XXXVIII},
 volume={9599},
 pages={959912},
 year={2015},
 organization={International Society for Optics and Photonics}
}

Copyright:

—— COPYRIGHT NOTICE, CONDITIONS, AND DISCLAIMER START WITH THIS LINE —————–
Copyright (c) 2009-2015 Arizona Board of Regents.  All Rights Reserved.
Contact: Lina Karam ([email protected]) and Milind Gide ([email protected]) 
Image, Video, and Usabilty (IVU) Lab, http://ivulab.asu.edu , Arizona State University
This copyright notice must also be included in any file or product that is derived from the database.
Redistribution and use of the SynTEX Granularity Database  database, without modification, are permitted provided that the following conditions are met: 
– Redistribution’s of the database  must retain the above copyright notice, this list of conditions and the following disclaimer.
– Redistribution’s in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
– The Image, Video, and Usability Laboratory (IVU Lab, http://ivulab.asu.edu) is acknowledged in any publication that reports research results using this database, copies of this database, or modifications of this database. 
Our paper is to be cited as follows:

Golestaneh, S. Alireza, Mahesh M. Subedar, and Lina J. Karam. “The effect of texture granularity on texture synthesis quality.” Applications of Digital Image Processing XXXVIII. Vol. 9599. International Society for Optics and Photonics, 2015.
Bibtex Entry : 
@inproceedings{golestaneh2015effect,
title={The effect of texture granularity on texture synthesis quality},
author={Golestaneh, S Alireza and Subedar, Mahesh M and Karam, Lina J},
booktitle={Applications of Digital Image Processing XXXVIII},
volume={9599},
pages={959912},
year={2015},
organization={International Society for Optics and Photonics}
}
DISCLAIMER:
This database is provided by the copyright holders and contributors “as is” and any express or implied warranties, including, but not limited to, the implied warranties of merchantability and fitness for a particular purpose are disclaimed.
In no event shall the Arizona Board of Regents, Arizona State University, IVU Lab members, authors or contributors be liable for any direct, indirect, incidental, special, exemplary, or consequential damages (including, but not limited to, procurement of substitute goods or services; loss of use, data, or profits; or business interruption) however caused and on any theory of liability, whether in contract, strict liability, or tort (including negligence or otherwise) arising in any way out of the use of this database, even if advised of the possibility of such damage. 
—— COPYRIGHT NOTICE, CONDITIONS, AND DISCLAIMER END WITH THIS LINE —————–

Downloading the Database:

 By downloading the SynTEX Granularity Database, you agree to the above COPYRIGHT NOTICE, CONDITIONS, AND DISCLAIMER. 

The entire database which includes all the images and the raw subjective scores can be downloaded by clicking here.