Abstract
In video coding, the sum of squared differences (SSD) is traditionally used for rate-distortion optimization (RDO). However, SSD has been known that has low correlation on subjective quality. In particular, film grain noise (FGN)-synthesized video sequence is a very good example of subjective quality degradation with SSD-based RDO. Therefore, structural similarity (SSIM) has been considered for RDO owing to its simplicity and high correlation with subjective quality. The SSIM metric was not designed to be used for previous RDO framework; additional processing, such as content analysis or adaptive Lagrangian multipliers, was required in previous studies. Based on analyzing cases of degradation in SSIM-based coding, this study proposes a novel SSIM-like distortion measure. In this paper, two objectives are considered. First one is FGN-synthesized video coding using the SSIM-like distortion measure to preserve noise pattern. Seconds, the proposed metric is designed for direct application in previously developed RDO frameworks without scene-analysis-based RDO. The experimental results demonstrate that the proposed method reduces erroneous prediction blocks and the Bjøntegaard delta rate by 67.46% on average compared to original SSIM-based RDO for FGN-synthesized video sequences. The results show the proposed metric is effective for film grain noise in similar bit rate, compared to a high-efficiency video coding test model (HM16.6) and the original SSIM metric.
Similar content being viewed by others
References
Aflaki, P., Hannuksela, M.M., Gabbouj, M.: Subjective quality assessment of asymmetric stereoscopic 3D video. Signal Image Video Process. 9(2), 331–345 (2015)
Bae, S.H., Kim, M.: A novel DCT-based JND model for luminance adaptation effect in DCT frequency. IEEE Signal Process. Lett. 20(9), 893–896 (2013)
Bae, S.H., Kim, M.: A novel SSIM index for image quality assessment using a new luminance adaptation effect model in pixel intensity domain. In: 2015 Visual Communications and Image Processing (VCIP), pp. 1–4 (2015)
Bossen, F.: Common HM test conditions and software reference configurations. In: Document JCTVC-L1100. JCT-VC, Geneva
Chen, Z., Guillemot, C.: Perceptually-friendly H. 264/AVC video coding based on foveated just-noticeable-distortion model. IEEE Trans. Circuits Syst. Video Technol. 20, 806–819 (2010)
Chou, C., Li, Y.: A perceptually tuned subband image coder based on the measure of just-noticeable-distortion profile. IEEE Trans. Circuits Syst. Video Technol. 5, 467–476 (1995)
Dai, J., Au, O.C., Pang, C., Yang, W., Zou, F.: Film grain noise removal and synthesis in video coding. In: 2010 IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 890–893. IEEE (2010)
Dai, W., Au, O.C., Zhu, W., Wan, P., Hu, W., Zhou, J.: SSIM-based rate-distortion optimization in H.264. In: 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 7343–7347. IEEE (2014)
Dosselmann, R., Yang, X.D.: A comprehensive assessment of the structural similarity index. Signal Image Video Process. 5(1), 81–91 (2011)
Gomila, C., Kobilansky, A.: SEI message for film grain encoding. In: Document JVT-H220 (2003)
Hepper, D.: Investigating properties of film grain noise for film grain management. In: 2013 IEEE Third International Conference on Consumer Electronics Berlin (ICCE-Berlin), pp. 185–188. IEEE (2013)
Hore, A., Ziou, D.: Image quality metrics: PSNR vs. SSIM. In: 2010 20th International Conference on Pattern Recognition, pp. 2366–2369 (2010)
Huang, Y., Ou, T.S., Su, P.Y., Chen, H.H.: Perceptual rate-distortion optimization using structural similarity index as quality metric. IEEE Trans. Circuits Syst. Video Technol. 20(11), 1614–1624 (2010)
Joshi, Y.G., Loo, J., Shah, P., Rahman, S., Chang, Y.C.: A novel low complexity Local Hybrid Pseudo-SSIM-SATD distortion metric towards perceptual rate control. In: 2013 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB), pp. 1–6 (2013)
Nikvand, N., Wang, Z.: Image distortion analysis based on normalized perceptual information distance. Signal Image Video Process. 7(3), 403–410 (2013)
Oh, B.T., Lei, S.M., Kuo, C.C.: Advanced film grain noise extraction and synthesis for high-definition video coding. IEEE Trans. Circuits Syst. Video Technol. 19(12), 1717–1729 (2009)
Ou, T.S., Huang, Y.H., Chen, H.H.: A perceptual-based approach to bit allocation for H.264 encoder. In: Frossard, P., Li, H., Wu, F., Girod, B., Li, S., Wei, G. (eds.) Visual Communications and Image Processing 2010, pp. 77,441B–77,441B-10. International Society for Optics and Photonics, Bellingham (2010)
Rehman, A., Wang, Z.: SSIM-inspired perceptual video coding for HEVC. In: 2012 IEEE International Conference on Multimedia and Expo, pp. 497–502 (2012)
Rosewarne, C., Bross, B., Naccari, M., Sharman, K., Sullivan, G.: High efficiency video coding (HEVC) test model 16 (HM 16) improved encoder description update 2. In: Document JCTVC-T1002. JCT-VC, Geneva
Schlockermann, M., Wittmann, S., Wedi, T., Kadono, S.: Film grain coding in H. 264/AVC. In: Document JVT-I034 (2003)
Sullivan, G., Wiegand, T.: Rate-distortion optimization for video compression. IEEE Signal Process. Mag. 15(6), 74–90 (1998)
Sullivan, G.J., Ohm, J.R., Han, W.J., Wiegand, T.: Overview of the high efficiency video coding (HEVC) standard. IEEE Trans. Circuits Syst. Video Technol. 22(12), 1649–1668 (2012)
Wang, J., Yu, X., He, D.: On BD-rate calculation. In: Document JCTVC-F270
Wang, S., Rehman, A., Wang, Z., Ma, S., Gao, W.: SSIM-motivated rate-distortion optimization for video coding. IEEE Trans. Circuits Syst. Video Technol. 22(4), 516–529 (2012)
Wang, S., Rehman, A., Wang, Z., Ma, S., Gao, W.: Perceptual video coding based on SSIM-inspired divisive normalization. IEEE Trans. Image Process. 22(4), 1418–1429 (2013)
Wang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P.: Image quality assessment: from error visibility to structural similarity. IEEE Trans. Image Process. 13(4), 600–12 (2004)
Wiegand, T., Schwarz, H., Joch, A., Kossentini, F., Sullivan, G.: Rate-constrained coder control and comparison of video coding standards. IEEE Trans. Circuits Syst. Video Technol. 13(7), 688–703 (2003)
Yeo, C., Tan, H.L., Tan, Y.H.: On rate distortion optimization using SSIM. IEEE Trans. Circuits Syst. Video Technol. 23(7), 1170–1181 (2013)
Zhao, P., Liu, Y., Liu, J., Yao, R., Ci, S., Tang, H.: Low-complexity content-adaptive Lagrange multiplier decision for SSIM-based RD-optimized video coding. In: 2013 IEEE International Symposium on Circuits and Systems (ISCAS2013), pp. 485–488. IEEE (2013)
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Kim, S., Pak, D. & Lee, S. SSIM-based distortion metric for film grain noise in HEVC. SIViP 12, 489–496 (2018). https://doi.org/10.1007/s11760-017-1184-6
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11760-017-1184-6