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Investigation of Image Quality of Dirac, H.264 and H.265

Investigation of Image Quality of Dirac, H.264 and H.265. Biju Shrestha UTA ID: 1000113697 Email: biju.shrestha@mavs.uta.edu. Overview. Introduction Dirac H.264 H.265 Image quality a ssessment using SSIM and FSIM SSIM – structural similarity metric FSIM – featured similarity index

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Investigation of Image Quality of Dirac, H.264 and H.265

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  1. Investigation of Image Quality of Dirac, H.264 and H.265 Biju Shrestha UTA ID: 1000113697 Email: biju.shrestha@mavs.uta.edu EE 5359: Multimedia Processing

  2. Overview • Introduction • Dirac • H.264 • H.265 • Image quality assessment using SSIM and FSIM • SSIM – structural similarity metric • FSIM – featured similarity index • Conclusion • References

  3. Introduction • Video codec compress/decompress digital video • Types of video codecs • Dirac • H.264 • H.265 Source: [2]

  4. Dirac • Developed by BBC (British Broadcasting Corporation) Research and is open source • Powerful and flexible despite using less number of core tools [1] • Features [1] • Multi-resolution transforms • Inter and intra frame coding • Frame and field coding • Dual syntax • CBR (constant bit rate) and VBR (variable bit rate) operations • Variable bit depths. • Multiple chromasampling formats • Lossless and lossycoding • Choice of wavelet filters • Simple stream navigation Source: [1]

  5. Dirac Encoder Architecture Source: [15]

  6. Dirac Decoder Architecture Source: [18]

  7. H.264 • Also referred as AVC (advance video coding) is a standard for video compression [2] • Joint development of video coding experts group (VCEG) of the ITU-T* and the moving picture experts group (MPEG) of ISO/IEC* [11] • Enhanced coding efficiency • Applications - video telephony, video conferencing, TV, storage, streaming video, digital video authoring, digital cinema, etc. [11] *ITU-T : international telecommunication union – telecommunication standardization sector *ISO : international organization for standardization *IEC : international engineering consortium Source: [2, 11]

  8. H.264 Decoder Block Diagram Source: [2]

  9. H.264 Encoder Block Diagram Source: [2]

  10. H.264 Profiles Source: [12]

  11. H.265 • Also known as high efficiency video coding (HEVC) [3] • Can deliver significant improvement relative to AVC (ITU-T* H.264 | ISO/IEC 14496-10) [10] • Efficiency can be progressed by average of 37 % for hierarchical B structure and 36 % for IPPP structure [16] • Video codec is composed of many processes including intra prediction and inter prediction, transforms, quantization, entropy coding, and filtering [17] *ITU-T: international telecommunication union – telecommunication standardization sector Source: [3, 10, 16, 17]

  12. H.265 Encoder Block Diagram Grey boxes – Proposed tools White boxes – H.264/AVC tools *IST : integer sine transform Source: [17]

  13. H.265 Decoder Block Diagram Grey boxes – Proposed tools White boxes – H.264/AVC tools Source: [27]

  14. Image Quality Assessment • Digital images and videos are prone to several distortion [5] • Nonstructural distortion • Structural distortion • Phases when distortion occurs [5] • Acquisition • Processing • Compressing • Storage • Transmission • Reproduction • Results of distortion – poor visual quality [5] • Different metrics available to quantify visual quality [3, 8, 13, 14] Source: [3, 5, 8, 13, 14]

  15. Nonstructural and Structural Distortions Source: [14]

  16. Comparison Metrics • FSIM – Featured Similarity index • SSIM – Structural Similarity metric • Bit rate • PSNR – Peak Signal to Noise Ratio • MSE – Mean Squared Error

  17. FSIM/FSIMc • Based on human visual system (HVS) • FSIM is designed for gray-scale images • FSIMc incorporates chrominance information • Mathematical model of FSIM • SL(x) = overall similarity between f1(x) and f2(x) • Mathematical model of FSIMc • λ > 0 is the parameter used to adjust the importance of the chrominance components. Source: [3]

  18. FSIM/FSIMc Index Computation f1 is the reference image, and f2 is a distorted version of f1 [3]. Source: [3]

  19. SSIM • Based on degradation of structural information [5] • HVS is adapted to extract structural information from an images [14] Source: [5, 14] Figure: Block diagram of structural similarity (SSIM) measurement system [5]

  20. Mathematical Representation of SSIM • General form of SSIM • α, β, and γ are parameters that mediate the relative importance of the three components • µx and µy = local sample means of x and y respectively • σxand σy= local sample standard deviations of x and y respectively • σxy = local sample correlation coefficient between x and y • C1, C2, and C3 = constants that stabilize the computations when denominators become small • Using α = β = γ = 1. We get, Source: [7]

  21. PSNR and MSE • Both are directly dependent on the intensity of an image [3] • Both do not correlate with subjective fidelity ratings [3] • Both cannot model human visual system very accurately [4] Source: [3, 4]

  22. Example: SSIM and MSE *MSE is approximately same for all images but SSIM is different giving better comparison[13] Source: [13, 22]

  23. Ranking of Image Quality Assessment Metrics • Different metrics take different approach to quantify images • Ranking of metrics by different databases Table : Ranking of image quality assessment metrics performance on six databases[5] Source: [3]

  24. Results • Video Information • QCIF sequence: foreman_qcif.yuv • Frame height: 176 • Frame width: 144 • Frame rate: 30 frame/second Source: [28]

  25. Results from H.264 Footer Text

  26. Results from Dirac

  27. MSU Video Quality Measurement Tool 3.0 • Open source video quality measurement tool • Calculate different metrics like PSNR, SSIM, MSSSIM, and MSE

  28. Conclusion • Measurement of metrics like PSNR, MSE, SSIM, and MS SSIM respectively for various bitrates for foreman QCIF sequence using H.264 encoder and Dirac encoder was performed • Further measurement of metrics using H.265 is needed to do comparative analysis • Comparative metrics like PSNR, MSE, SSIM, MS SSIM, and FSIM at various bitrates are being used • Based on various test sequences, the performance of codec will be investigated • Software and tools that will be used: • MATLAB • Visual studio • JM software • KTA software • Dirac Pro • MSU VQMT (Moscow State University video quality measurement tool) Source: [19 - 24]

  29. References [1] Dirac Video (2008, September 23), “Dirac Specification”[Online]. Available: http://diracvideo.org/download/specification/dirac-spec-latest.pdf [2] I. Richardson (2011), “A Technical Introduction to H.264/AVC” [Online]. Available: http://www.vcodex.com/files/H.264_technical_introduction.pdf [3] L. Zhang, L. Zhang, X. Mou, and D. Zhang,“FSIM: A feature similarity index for image quality assessment,” IEEE Transactions on Image Processing, vol.20, no.8, pp.2378-2386, Aug. 2011. [4] Z.Liand A.M. Tourapis, “New video quality metrics in the H.264 reference software,” Input Document to JVT, Hannover, DE, 20-25 Jul. 2008. [5] Z. Wang, A.C. Bovik, H.R. Sheikh, and E.P. Simoncelli,“Image quality assessment: from error visibility to structural similarity,” IEEE Transactions on Image Processing, vol. 13, issue 4, pp. 600-612, Apr. 2004. [6] Z. Wang, E.P. Simoncelli, and A.C. Bovik, “Multiscale structural similarity for image quality assessment,” Conference Record of the Thirty-Seventh Asilomar Conference on Signals, Systems and Computers, 2003, vol.2, pp. 1398- 1402, 9-12 Nov. 2003. [7] C. Li, and A. C. Bovik, “Content-weighted video quality assessment using a three-component image model.” Journal of Electronic Imaging, vol.19, pp. 65-71, Mar. 2010. [8] X. Ran and N. Farvardin, “A perceptually-motivated three-component image model - part I: description of the model,” IEEE Transactions on Image Processing, vol.4, no.4, pp.401-415, Apr. 1995. [9] J. L. Li, G. Chen, and Z. R. Chi, “Image coding quality assessment using fuzzy integrals with a three-component image model,” IEEE Transactions on Fuzzy Systems, vol.12, no.1, pp. 99- 106, Feb. 2004. [10] G. J. Sullivan and J. Ohm, “Recent developments in standardization of high efficiency video coding (HEVC),” Proc. SPIE 7798, 77980V, 2010. [11] G. Sullivan, P. Topiwalla, and A. Luthra, “The H.264/AVC video coding standard: overview and introduction to the fidelity range extensions,” SPIE Conference on Applications of Digital Image Processing XXVII, vol. 5558, pp. 53-74, Aug. 2004. [12] A. Puri, X. Chen, and A. Luthra, “Video coding using the H.264/MPEG-4 AVC compression standard,” Signal Processing: Image Communication, vol. 19, pp. 793-849, Oct. 2004.

  30. References [13] Z. Wang et al (2003, February), “The SSIM index for image quality assessment” [Online]. Available: https://ece.uwaterloo.ca/~z70wang/research/ssim/ [14] C. Chukka, “A universal image quality index and SSIM comparison”[Online]. Available: http://www-ee.uta.edu/Dip/Courses/EE5359/chaitanyaee5359d.pdf [15] BBC Research, “The technology behind Dirac” [Online]. Available: http://www.bbc.co.uk/rd/projects/dirac/technology.shtml [16] E. Alshina et al, “Technical considerations of new challenges in video coding standardization,” International Organization for Standardization Organization Internationale De Normalisation ISO/IEC JTC1/SC29/WG11 Coding of Moving Pictures and Audio, Oct. 2008. [17] S. Jeong et al, “Highly efficient video codec for entertainment quality,” ETRI Journal, vol.33, no. 2, pp. 145-154, Apr. 2011. [18] K. R. Rao and D. N. Kim, “Current video coding standards: H.264/AVC, Dirac, AVS China and VC-1,” 42nd Southeastern Symposium on System Theory (SSST), pp.1-8, Mar. 2010. [19] A. M. Tourapis (January 2009), “H.264/14496-10 AVC reference software manual”[Online]. Available: http://iphome.hhi.de/suehring/tml/JM%20Reference%20Software%20Manual%20%28JVT-AE010%29.pdf [20] F. Bossen, D. Flynn, and K. Sühring (July 2011), “HEVC reference software manual” [Online]. Available: http://phenix.int-evry.fr/jct/doc_end_user/documents/6_Torino/wg11/JCTVC-F634-v2.zip [21] DiracPROsoftware: http://dirac.kw.bbc.co.uk/download/ [22] D. T. Lee, “JPEG 2000: Retrospective and new developments,” Proc. IEEE, vol. 93, pp. 32-41, Jan. 2005. [23] KTA software: http://iphome.hhi.de/suehring/tml/download/KTA/ [24] H.264/AVC Reference Software: http://iphome.hhi.de/suehring/tml/download/ [25] A. Ravi, “Performance analysis and comparison of the Dirac video codec with H.264/MPEG-4 part 10 AVC,” M.S. thesis, Dept. Elect. Eng., Univ. of Texas at Arlington, 2009 [25] I.E.G. Richardson, “H.264 and MPEG-4 video compression: video coding for next generation multimedia,” Great Britain: Wiley, 2003, pp. 159-223 [26] MSU video quality measurement tool: http://compression.ru/video/quality_measure/video_measurement_tool_en.html [27] B. Bross et al, “High efficiency video coding (HEVC) text specification draft 6,” Joint collaborative Team on Video Coding (JCT-VC) of ITU-T SG16 WP3 and ISO/IEC JTC1/SC29/WG11, 7th Meeting: Geneva, CH, 21–30 Nov. 2011. [28] “YUV video sequences” [Online]. Available: http://trace.eas.asu.edu/yuv/

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