FPGA Implementation of Procedures for Video Quality Assessment
DOI:
https://doi.org/10.7494/csci.2018.19.3.2825Keywords:
Video quality, video metrics, image processing, FPGA, Impulse CAbstract
Video resolutions used in a variety of media are constantly rising. While manufacturers struggle to perfect their screens, it is also important to ensure high quality of displayed image. Overall quality can be measured using Mean Opinion Score (MOS). Video quality can be aected by miscellaneous artifacts, appearing at every stage of video creation and transmission. In this paper, we present a solution to calculate four distinct video quality metrics that can be applied to a real-time video quality assessment system. Our assessment module is capable of processing 8K resolution in real time set at the level of 30 frames per second. The throughput of 2.19 GB/s surpasses the performance of pure software solutions. The module was created using a high-level language to concentrate on the architectural optimization.Downloads
References
Bodenner R.: Creating Platform Support Packages, 2011. URL http://www.impulseaccelerated.com/AppNotes/APP109_PSP/IATAPP109_PSP.pdf. Accessed: 23.06.2016.
Cerqueira E., Janowski L., Leszczuk M., Papir Z., Romaniak P.: Video Artifacts Assessment for Live Mobile Streaming Applications. In: A. Mauthe, S. Zeadally,E. Cerqueira, M. Curado, eds., Future Multimedia Networking, Lecture Notes in Computer Science, vol. 5630, pp. 242{247. Springer Berlin Heidelberg, 2009. ISBN 978-3-642-02471-9. URL http://dx.doi.org/10.1007/978-3-642-02472-6_26.
Farias M.C., Mitra S.K.: No-reference video quality metric based on artifact measurements. In: Image Processing, vol. 3, pp. III{141{4, 2005. URL http://dx.doi.org/10.1109/ICIP.2005.1530348.
Farias M.C.Q., Heynderickx I., Macchiavello Espinoza B.L., Redi J.A.: Visual
Artifacts Interference Understanding and Modeling (VARIUM). In: Seventh International Workshop on Video Processing and Quality Metrics for Consumer Electronics, vol. 1. Scottsdale, 2013.
Farias M.C.Q., Mitra S.K.: Perceptual contributions of blocky, blurry, noisy,
and ringing synthetic artifacts to overall annoyance. In: Journal of Electronic Imaging, vol. 21(4), pp. 043013{043013, 2012. URL http://dx.doi.org/10.1117/1.JEI.21.4.043013.
Gustafsson J., Heikkila G., Pettersson M.: Measuring multimedia quality in mobile networks with an objective parametric model. In: Image Processing, 2008.ICIP 2008. 15th IEEE International Conference on, pp. 405
Moore G.W.: Flatterland. Like Flatland. Only More So.: I. Stewart; Perseus
Publishing Cambridge, MA, 2001, pp 301, ISBN 0-7382-0442-0. In: Neurocomputing, vol. 42(1-4), pp. 337
Mu M., Romaniak P., Mauthe A., Leszczuk M., Janowski L., Cerqueira E.:
Framework for the integrated video quality assessment. In: MULTIMEDIA
TOOLS AND APPLICATIONS, vol. 61(3), pp. 787-817, 2012. ISSN 1380-7501. http://dx.doi.org/10.1007/s11042-011-0946-3.
Neborovski E., Marinkovic V., Katona M.: Video quality assessment approach with field programmable gate arrays. In: The 33rd International Convention MIPRO, pp. 713-717, 2010.
de Oliveira M., da Silva W., Fonseca K.V.O., Pohl A.D.A.P.: VHDL implementation of a No-Reference video quality metric using the Levenberg-Marquardt method. In: International Symposium on Broadband Multimedia Systems and Broadcasting, pp. 1{5, 2014. URL http://dx.doi.org/10.1109/BMSB.2014.6873474.
Papu J.J., See H.: Design of a Reconfigurable Computing Platform. In: Proceedings of Innovative Technologies in Intelligent Systems and Industrial Applications, pp. 148-153, 2009.
Pellerin D., Thibault S.: Practical FPGA programming in C. In: Upper Saddle
River, NJ Prentice Hall Press, 2005.
Punchihewa A., Bailey D.G.: Artefacts in Image and Video Systems: Classification and Mitigation. In: Image and Vision Computing New Zealand. 2002.
Rohaly A.M., Corriveau P., Libert J., Webster A., Baroncini V., Beerends J.,
Blin J.L.: Video Quality Experts Group: Current Results and Future Directions, 2000.
Romaniak P.: Assessment of perceptual video quality affected by acquisition and bit-rate reduction artifacts. Ph.d. thesis, 2011.
Romaniak P., Janowski L., Leszczuk M., Papir Z.: A no reference metric for
the quality assessment of videos affected by exposure distortion. In: Multimedia and Expo (ICME), 2011 IEEE International Conference on, pp. 1-6. 2011. ISSN 1945-7871. URL http://dx.doi.org/10.1109/ICME.2011.6011903.
Romaniak P., Janowski L., Leszczuk M., Papir Z.: Perceptual quality assessment for H.264/AVC compression. In: Consumer Communications and Networking Conference (CCNC), 2012 IEEE, pp. 597-602. 2012. ISSN Pending.
Takahashi A., Yamagishi K., Kawaguti G.: Global Standardization Activities Recent Activities of QoS / QoE Standardization in ITU-T SG12. In: Ntt Technical Review, vol. 6(9), pp. 1|5, 2008.
Wielgosz M., Panggabean M., Chilwan A., Ronningen L.A.: FPGA-Based Platform for Real-Time Internet. In: A. Stoica, D. Zarzhitsky, G. Howells, C.D. Frowd, K.D. McDonald-Maier, A.T. Erdogan, T. Arslan, eds., EST, pp. 131-134. IEEE Computer Society, 2012. ISBN 978-1-4673-2448-9. URL http://dx.doi.org/10.1109/EST.2012.18.
Wielgosz M., Panggabean M., Ronningen L.A.: FPGA Architecture for Kriging
Image Interpolation. In: International Journal of Advanced Computer Science and Applications(IJACSA), vol. 4(12), 2013. URL http://ijacsa.thesai.org/.
Wielgosz M., Panggabean M., Wang J., Ronningen L.A.: An FPGA-Based Platform for a Network Architecture with Delay Guarantee. In: Journal of Circuits, Systems, and Computers, vol. 22(6), 2013. URL http://dx.doi.org/10.1142/S021812661350045X.
Wyckens E.: Proposal studies on new video metrics. In: A. Webster, ed., VQEG Hillsboro Meeting, p. 17. Orange Labs, Video Quality Experts Group (VQEG), Hillsboro, 2011.