Abstract
A large number of Image Quality (IQ) metrics have been developed over the last decades and the number continues to grow. For development and evaluation of such metrics, IQ databases with reference images, distortions, and perceptual quality data, is very useful. However, existing IQ databases have some drawbacks, making them incapable of evaluating properly all aspects of IQ metrics. The lack of reference image design principles; limited distortion aspects; and uncontrolled viewing conditions. Furthermore, same sets of images are always used for evaluating IQ metrics, so more images are needed. These are some of the reasons why a newly developed IQ database is desired. In this study we propose a new IQ database, Colourlab Image Database: Image Quality (CID:IQ), for which we have proposed methods to design reference images, and different types of distortions have been applied. Another new feature with our database is that we have conducted the perceptual experiments at two viewing distances. The CID:IQ database is available at http://www.colourlab.no/cid .
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Ponomarenko, N., Lukin, V., Zelensky, A., Egiazarian, K., Carli, M., Battisti, F.: Tampere image database 2008, TID 2008 (2008), http://www.ponomarenko.info/tid2008.htm
Sheikh, H., Wang, Z., Cormack, L., Bovik, A.: LIVE image quality assessment database release 2 (2006), http://live.ece.utexas.edu/research/quality
Tourancheau, S., Autrusseau, F., Sazzad, Z.M.P., Horitaa, Y.: MICT image quality evaluation database (2008), http://mict.eng.u-toyama.ac.jp/mictdb.html
Le Callet, P., Autrusseau, F.: Subjective quality assessment Irccyn/IVC database (2005), http://www2.irccyn.ec-nantes.fr/ivcdb/
Larson, E.C., Chandler, D.: Categorical subjective image quality CSIQ database (2010), http://vision.okstate.edu/?loc=csiq
Zaric, A., Tatalovic, N., Brajkovic, N., Hlevnjak, H., Loncaric, M., Dumic, E., Grgic, S.: VCLFER image quality assessment database (2011), http://www.vcl.fer.hr/quality/
Field, G.G.: Test image design guidelines for color quality evaluation. In: Color and Imaging Conference, Scottsdale, Arizona, USA, pp. 194–196 (November 1999)
Keelan, B.W., Urabe, H.: ISO 20462: A psychophysical image quality measurement standard. In: SPIE Proceedings, vol. 5294, pp. 181–189. Image Quality and System Performance (2003)
ISO. 2004. ISO 20462-1 photography - psychophysical experimental methods to estimate image quality - part 1: Overview of psychophysical elements
Winkler, S.: Analysis of public image and video databases for quality assessment. IEEE Journal of Selected Topics in Signal Processing 6(6), 616–625 (2012)
Orfanidou, M., Triantaphillidou, S., Allen, E.: Predicting image quality using a modular image difference model. In: SPIE Proceedings 2008, Image Quality and System Performance (January 2008)
De Simone, F., Goldmann, L., Baroncini, V., Ebrahimi, T.: JPEG core experiment for the evaluation of JPEG XR image (2009), http://mmspg.epfl.ch/iqa
CIE. 2004 Guidelines for the evaluation of gamut mapping algorithms. Technical Report. ISBN: 3-901-906-26-6, CIE TC8-03, 156
Farup, I., Hardeberg, J.Y., Bakke, A.M., Kopperud, S., Rindal, A.: Visualization and interactive manipulation of color gamuts. In: Color Imaging Conference, Scottsdale, Arizona, USA, pp. 250–255 (November 2002)
ITU. Recommendation BT.500 : Methodology for the subjective assessment of the quality of television pictures. International Telecommunication Union, Geneva, Switzerland, 53-56 (2002)
Engeldrum, P.G.: Psychometric scaling: A toolkit for imaging systems development. Imcotek Press (2000)
Liu, X.: CID:IQ - a new image quality database. Master thesis, Gjøvik University College (2013)
Hardeberg, J.Y., Bando, E., Pedersen, M.: Evaluating colour image difference metrics for gamut-mapped images. Coloration Technology 124(4), 243–253 (2008)
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Liu, X., Pedersen, M., Hardeberg, J.Y. (2014). CID:IQ – A New Image Quality Database. In: Elmoataz, A., Lezoray, O., Nouboud, F., Mammass, D. (eds) Image and Signal Processing. ICISP 2014. Lecture Notes in Computer Science, vol 8509. Springer, Cham. https://doi.org/10.1007/978-3-319-07998-1_22
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DOI: https://doi.org/10.1007/978-3-319-07998-1_22
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