DOI QR코드

DOI QR Code

Subjective Video Quality Evaluation of H.265/HEVC Encoded Low Resolution Videos for Ultra-Low Band Transmission System

초협대역 전송 시스템상에서 H.265/HEVC 부호화 저해상도 비디오에 대한 주관적 화질 평가

  • Uddina, A.F.M. Shahab (Department of Computer Science and Engineering, Kyung Hee University) ;
  • Monira, Mst. Sirazam (Department of Computer Science and Engineering, Kyung Hee University) ;
  • Chung, TaeChoong (Department of Computer Science and Engineering, Kyung Hee University) ;
  • Kim, Donghyun (Agency for Defense Development) ;
  • Choi, Jeung Won (Agency for Defense Development) ;
  • Jun, Ki Nam (LIG Nex1) ;
  • Bae, Sung-Ho (Department of Computer Science and Engineering, Kyung Hee University)
  • Received : 2019.07.12
  • Accepted : 2019.09.06
  • Published : 2019.11.30

Abstract

In this paper, we perform a subjective quality assessment on low-resolution surveillance videos, which are encoded with a very low target bit-rate to use in an ultra-low band transmission system and investigate the encoding effects on the perceived video quality. The test videos are collected based on their spatial and temporal characteristics which affect the perceived quality. H.265/HEVC encoder is used to prepare the impaired sequences for three target bit-rates 20, 45, and 65 kbps and subjective quality assessment is conducted to evaluate the quality from a viewing distance of 3H. The experimental results show that the quality of encoded videos, even at target bit-rate of 45 kbps can satisfy the users. Also we compare objective image/video quality assessment methods on the proposed dataset to measure their correlation with subjective scores. The experimental results show that the existing methods poorly performed, that indicates the need for a better quality assessment method.

본 논문에서는 저해상도 감시(surveillance) 비디오에 대한 주관적 화질 평가를 수행한다. 본 논문은 저해상도 영상에 맞는 초협대역 전송 환경을 고려하여 비디오 압축을 수행한 다음, 압축된 비디오의 주관적 화질 성능을 측정하였다. 데이터의 일반성을 확보하기 위해 다양한 시/공간 복잡도를 가지는 감시 비디오를 수집하였다. 저해상도 감시 비디오 압축은 H.265/HEVC로 수행되었으며 3개의 목표 비트(20, 45, 65 kbps)에 대해 압축을 수행했다. 주관적 화질 평가 결과, 수집한 대부분의 저해상도 감시 비디오는 45 kbps이상으로 압축될 경우 주관적 화질 열화가 거의 발생하지 않는 것으로 나타났다. 뿐만 아니라, 기존 개발된 객관적 영상 화질 측정 방법을 이용해 예측된 화질과의 상관관계를 비교하는 실험을 진행했고, 실험 결과 현존하는 대부분의 객관적 화질 측정 방법이 초협대역 전송 조건에서 저해상도 감시 비디오의 화질을 제대로 예측하지 못하는 것을 확인하였다. 이는 초협대역 전송 기반 저해상도 감시 비디오에 대한 새로운 객관적 영상 화질측정 기법이 개발되어야 함을 시사한다.

Keywords

References

  1. G. J. Sullivan and J.-R. Ohm, "Recent developments in standardization of high efficiency video coding (HEVC)," Proceeding of SPIE, vol. 7798. Aug. 2010, paper 7798-30, https://doi.org/10.1117/12.863486.
  2. The Moving Picture Experts Group, https://mpeg.chiariglione.org/
  3. Test Materials to Be Used in Subjective Assessment of picture quality, ITU-R BT.1210, International Telecommunications Union, Feb. 2004.
  4. C. S. Won, D. K. Park, and S.-J. Park, "Efficient use of MPEG-7 edge histogram descriptor," Electronics and Telecommunications Research Institute Journal, vol. 24, no. 1, pp. 23-30, Feb. 2002, https://doi.org/10.4218/etrij.02.0102.0103.
  5. K. Seshadrinathan, R. Soundararajan, A. C. Bovik and L. K. Cormack, "Study of Subjective and Objective Quality Assessment of Video", IEEE Transactions on Image Processing, vol.19, no.6, pp.1427-1441, June 2010, https://doi.org/10.1109/TIP.2010.2042111.
  6. P. V. Vu and D. M. Chandler, "ViS3: An Algorithm for Video Quality Assessment via Analysis of Spatial and Spatiotemporal Slices," Journal of Electronic Imaging, 23 (1), 01316, 2014, https://doi.org/10.1117/1.JEI.23.1.013016.
  7. C. G. Bampis, Z.Li, I. Katsavounidis, TY Huang, C. Ekanadham and A. C. Bovik, "Towards Perceptually Optimized End-to-end Adaptive Video Streaming," submitted to IEEE Transactions on Image Processing, 2018, https://arxiv.org/abs/1808.03898.
  8. Gary J Sullivan, Jensrainer Ohm,Woojin Han, and ThomasWiegand, "Overview of the high efficiency video coding (HEVC) standard," IEEE Transactions on Circuits and Systems for Video Technology, vol. 22, no. 12, pp. 1649-1668, 2012, https://doi.org/10.1109/TCSVT.2012.2221191.
  9. Methodology for the Subjective Assessment of the Quality of TV Pictures, ITU-R BT.500-11, International Telecommunications Union, Jun. 2002.
  10. 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, no. 4, pp. 600-612, Apr. 2004, https://doi.org/10.1109/TIP.2003.819861.
  11. Zhou Wang and A. C. Bovik, "A universal image quality index," in IEEE Signal Processing Letters, vol. 9, no. 3, pp. 81-84, March 2002, https://doi.org/10.1109/97.995823.
  12. L. Zhang, L. Zhang and X. Mou, "RFSIM: A feature based image quality assessment metric using Riesz transforms," 2010 IEEE International Conference on Image Processing, Hong Kong, 2010, pp. 321-324, https://doi.org/10.1109/ICIP.2010.5649275.
  13. W. Xue, L. Zhang, X. Mou and A. C. Bovik, "Gradient Magnitude Similarity Deviation: A Highly Efficient Perceptual Image Quality Index," in IEEE Transactions on Image Processing, vol. 23, no. 2, pp. 684-695, Feb. 2014, https://doi.org/10.1109/TIP.2013.2293423.
  14. L. Zhang, Y. Shen and H. Li, "VSI: A Visual Saliency-Induced Index for Perceptual Image Quality Assessment," in IEEE Transactions on Image Processing, vol. 23, no. 10, pp. 4270-4281, Oct. 2014, https://doi.org/10.1109/TIP.2014.2346028.
  15. S. Bae and M. Kim, "A Novel Image Quality Assessment With Globally and Locally Consilient Visual Quality Perception," in IEEE Transactions on Image Processing, vol. 25, no. 5, pp. 2392-2406, May 2016, https://doi.org/10.1109/TIP.2016.2545863.
  16. A. F. M. S. Uddin, T. C. Chung and S. Bae, "Visual saliency based structural contrast quality index," in IET Electronics Letters, vol. 55, no. 4, pp. 194-196, Feb. 2019, https://doi.org/10.1049/el.2018.6435.
  17. C. G. Bampis, P. Gupta, R. Soundararajan and A. C. Bovik, "SpEED-QA: Spatial Efficient Entropic Differencing for Image and Video Quality," in IEEE Signal Processing Letters, vol. 24, no. 9, pp. 1333-1337, Sept. 2017, https://doi.org/10.1109/LSP.2017.2726542.
  18. M. A. Aabed, G. Kwon and G. AlRegib, "Power of tempospatially unified spectral density for perceptual video quality assessment," 2017 IEEE International Conference on Multimedia and Expo (ICME), Hong Kong, 2017, pp. 1476-1481, https://doi.org/10.1109/ICME.2017.8019333.
  19. A. Mittal, M. A. Saad and A. C. Bovik, "A Completely Blind Video Integrity Oracle," in IEEE Transactions on Image Processing, vol. 25, no. 1, pp. 289-300, Jan. 2016, https://doi.org/10.1109/TIP.2015.2502725.