Wireless Imaging Quality (WIQ) Database
There have been increased efforts in recent years to objectively assess the quality of both, images and videos. The majority of works though have been focused on quality degradations due to lossy source coding. In a communication context, however, the quality may not solely be degraded during compression but also through bit errors or packet loss caused by the error prone transmission channel.
In case of source coding, the distortion types induced into the visual content are highly dependent on the source codec. For instance, JPEG encoded images are prone to blocking artifacts whereas JPEG2000 encoded images more likely experience blur and ringing artifacts. On the other hand, distortions caused by channel induced errors may result in more complex error patterns containing not only single artifacts at a time but instead varying combinations. In addition, source coding artifacts are typically fairly uniformly distributed whereas channel induced errors can cause strongly localized artifacts, both in the spatial and the temporal domain in case of video.
To address the problem of quality assessment for image communication we created a set of test images using a simulation model of a wireless link. We then conducted two subjective image quality tests of which the first one took place at the Western Australian Telecommunications Research Institute (WATRI) in Perth, Australia, and the second one at the Blekinge Institute of Technology (BTH) in Ronneby, Sweden. In each test, 30 non-expert viewers were persented 40 test images. We make the images used in the two tests and the corresponding subjective quality scores freely available to the image quality research community in the Wireless Imaging Quality (WIQ) database.
- Ulrich Engelke, Blekinge Institute of Technology, Sweden
- Tubagus Maulana Kusuma, Gunadarma University, Indonesia
- Hans-Jürgen Zepernick, Blekinge Institute of Technology, Sweden
The WIQ database is described in detail in  and  (copies of the papers can be obtained on request). The files that are included in the WIQ database are the following:
- The 7 reference images used in the subjective experiments
- The 80 distorted (test) images used in the subjective experiments
- The subjective scores for all 80 images obtained from the two subjective experiments
- A 'readme' file containing all information necessary to use the WIQ database
The WIQ database can be downloaded here:
- Reference images (wiq_ref_images.zip, approx. 1.55 MB)
- Distorted images from test 1(wiq_dst_images_t01.zip, approx. 8.88 MB)
- Distorted images from test 2 (wiq_dst_images_t02.zip, approx. 8.72 MB)
- Subjective scores, Matlab workspace (wiq_subjective_scores_matlab.zip, approx. 7 kB)
- Subjective scores, Excel spreadsheet (wiq_subjective_scores_excel.zip, approx. 45 kB)
- WIQ readme file (wiq_readme.zip, approx. 3 kB)
The ZIP files are password protected, please send an email to Ulrich Engelke (firstname.lastname@example.org) to obtain the password. A few lines about your background and the purpose of use of the WIQ database would be highly appreciated. If you use the WIQ database for your research, we kindly ask you to refer to our paper , and also to this website  (see Reference Information below).
 U. Engelke, M. Kusuma, H.-J. Zepernick, M. Caldera, "Reduced-Reference Metric Design for Objective Perceptual Quality Assessment in Wireless Imaging," Signal Processing: Image Communication, vol. 24, no. 7, pp. 525-547, 2009.
 U. Engelke, H.-J. Zepernick, and M. Kusuma, "Wireless Imaging Quality Database," http://www.bth.se/tek/rcg.nsf/pages/wiq-db, 2010.
Other related publications:
 U. Engelke, H.-J. Zepernick, T. M. Kusuma, "Subjective Quality Assessment for Wireless Image Communication: The Wireless Imaging Quality Database," Int. Workshop on Video Processing and Quality Metrics (VPQM), 2010.
 U. Engelke, H.-J. Zepernick, "Pareto Optimal Weighting of Structural Impairments for Wireless Imaging Quality Assessment," IEEE Int. Conf. on Image Processing (ICIP), 2008.
 U. Engelke, H.-J. Zepernick, "Multiobjective Optimization of Multiple Scale Visual Quality Processing," IEEE Int. Workshop on Multimedia Signal Processing (MMSP), 2008.
 U. Engelke, H.-J. Zepernick, "An Artificial Neural Network for Quality Assessment in Wireless Imaging Based on Extraction of Structural Information," IEEE Int. Conf. on Acoustics, Speech, and Signal Processing (ICASSP), 2007.
Permission is hereby granted, without written agreement and without license or royalty fees, to use, copy, modify, and distribute the data provided and its documentation for research purpose only. The data provided may not be commercially distributed. In no event shall the Blekinge Institute of Technology be liable to any party for direct, indirect, special, incidental, or consequential damages arising out of the use of the data and its documentation. The Blekinge Institute of Technology specifically disclaims any warranties. The data provided is on an "as is" basis and the Blekinge Institute of Technology has no obligation to provide maintenance, support, updates, enhancements, or modifications.