Measuring the effective coverage of the image databases

• Autorzy: Buczkowski M.
• Języki publikacji: EN

Abstrakty

EN

The paper presents new methods for estimating effective coverage of the image databases in spatial information (SI) vs. colorfulness (CF) space. Existing and commonly used metrics are vulnerable to databases containing very different images in terms of SI and CF, which can maximize the relative ranges, while preserving, in specific cases, high uniformity. The area covered by convex hull created on SI × CF space can be large, but the interior of the convex envelope might be poorly filled. To overcome this flaw, a fill factor is proposed, which determines how well the convex hull area is utilized. In the paper the method is described in details and presented on a few existing databases, as well as on artificial, non-existing databases to prove its robustness in different scenarios. Provided results show that new metric is closer to the actual coverage than existing methods.

Słowa kluczowe

EN

image quality assessment; coverage analysis; image characteristic analysis

• Wydawca: Wydawnictwo PAK
• Czasopismo: Measurement Automation Monitoring
• Rocznik: 2017
• Tom: Vol. 63, No. 5
• Strony: 183--185
• Opis fizyczny: Bibliogr. 11 poz., rys., tab., wzory

Twórcy

autor

Buczkowski M.

• Poznan University of Technology 3 Polanka St., 61-655 Poznan, Poland

Bibliografia

• [1] Liu X., Pedersen M., Hardeberg J. Y.: CID:IQ – A New Image Quality Database, vol. 8509, Springer, 2014.
• [2] Sheikh H. R., Wang Z., Cormack L., Bovik A. C.: LIVE Image Quality Assessment Database Release 2, http://live.ece.utexas.edu/research/
• [3] quality, Mar. 2017 .
• [4] Sheikh H. R., Sabir M. F., Bovik A. C.: A statistical evaluation of recent full reference image quality assessment algorithms. IEEE Transactions on Image Processing, vol. 15, no. 11, pp. 3440-3451, Nov. 2006.
• [5] Wang Z., Bovik A. C., Sheikh H. R., Simoncelli E. P.: Image quality assessment: from error visibility to structural similarity, IEEE Transactions on Image Processing, vol.13, no.4, pp. 600-612, Apr. 2004.
• [6] Ponomarenko N., Lukin V., Zelensky A., Egiazaarian K., Carli M., Battisiti F.: TID2008 – A Database for Evaluation Full-Reference Visual Quality Assessment Metrics, Advances of Modern Radioelectronics, vol. 10, pp. 30-45, 2009.
• [7] ANSI T1.801.03: Digital transport of one-way video signals – parameters for objective performance assessment. American National Standards Institute, 1996.
• [8] Hasler D., Susstrunk S.: Measuring colorfulness in natural images, Proc. SPIE Human Vision and Electronic Imaging vol. 5007, pp. 87-95, 2003.
• [9] Winkler S.: Analysis of Public Image and Video Databases for Quality Assessment. IEEE Selected Topics on Signal Processing, vol. 6, no. 6, pp. 616-625, 2012.
• [10] Buczkowski M., Stasinski R.: Effective Coverage as a New Metric for Image Quality Assessment Databases Comparison, Submitted to: International Conference on Systems, Signals and Image Processing , 2017, Poznan, Poland.
• [11] Delaunay B.: Sur la spheere vide. A la meemoire de Georges Voronoi, Bulletin de l’Academie des Sciences de l’URSS. Classe des sciences mathematiques et na, no. 6, pp. 793–800, 1934.

Uwagi

EN

Work founded by the Ministry of Science and Higher Education for the statutory activity of conduction research and development work and related tasks, contributing to the development of young scientists and doctoral students in 2017 under the project number 08/83/DSMK/4726.

PL

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).