A stereoscopic image consists of two views rendering a depth sense. Indeed each eye is constrained to look at one view, and the small objects displacements across the two views are interpreted as an indication of depth. These displacements are exploited as specific inter-view redundancies from a compression viewpoint. The classical still compression scheme, called disparity-compensated compression scheme, compresses one view independently of the second view, and a block-based disparity map modeling the displacements is losslessly compressed. The difference between the original view and its disparity predicted view is then compressed and used by the decoder to compute the compensated view to improve the disparity predicted view. However, a proof of concept work has already shown that selecting disparities according to the compensated view, instead of the predicted view, yields increased rate-distortion performance. This paper derives from the JPEG-coder, a disparity-dependent analytic expression of the distortion induced by the compensated view. This expression is embedded into an algorithm with a reasonable numerical complexity approaching the performance obtained with the proof of concept work. The proposed algorithm, called fast disparity-compensated block matching algorithm, provides at the same bitrate an average performance increase as compared to the classical stereoscopic image coding schemes.
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Nam, K., Anh-Hoang, P., Munkh-Uchral, E., Ashraful, AMd, Ki-Chul, K., Mei-Lan, P., Jeong-Hyeon, L.: 3D display technology. Disp. Imaging 1, 73–95 (2013)
Scharstein, D., Pal, C.: Learning conditional random fields for stereo. In: IEEE Conference on Computer Vision and Pattern Recognition, Minneapolis, MN, pp. 1–8 (2007)
Dufaux, F., Pesquet-Popescu, B., Cagnazzo, M.: Emerging Technologies for 3D Video: Creation, Coding, Transmission and Rendering, 1st edn. Wiley, Hoboken (2013)
Frossard, P., Schenkel, M.B., Luo, C., Wu, F.: Joint decoding of stereo jpeg image pairs. In: IEEE International Conference on Image Processing, pp. 2633–2636 (2010)
Ortis, A., Battiato, S.: A new fast matching method for adaptive compression of stereoscopic images. In Three-Dimensional Image Processing, Measurement (3DIPM), and Applications 2015. San Francisco, California, USA, February 10–12, p. 93930K (2015)
Ahlvers, Udo, Zölzer, Udo, Rechmeier, Stefan: FFT-based disparity estimation for stereo image coding. Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429), vol. 1, pp. I–761 (2003)
Schwarz, H., Bartnik, C., Bosse, S., Brust, H., Hinz, T., Lakshman, H., Marpe, D., Merkle, P., Müller, K., Rhee, H., Tech, G., Winken, M., Wiegand, T.: 3D video coding using advanced prediction, depth modeling, and encoder control methods. In: Picture Coding Symposium, pp. 1–4. (May 2012)
Li, S., Yu, M., Jiang, G., Choi, T.-Y., Kim, Y.-D.: Approaches to H. 264-based stereoscopic video coding. In: Third International Conference on Image and Graphics (ICIG’04), pp. 365–368 (Dec 2004)
Hanhart, P., Rerabek, M., Korshunov, P., Ebrahimi, T.: Subjective Evaluation of HEVC Intra Coding for Still Image Compression. Technical report, [JCT-VC contribution] AhG4, (Jan 2013)
Woo, W., Ortega, A.: Stereo image compression with disparity compensation using the MRF model. Vis. Commun. Image Process. 2727, 1–14 (1996)
Flierl, M., Mavlankar, A., Girod, B.: Motion and disparity compensated coding for multi-view video. IEEE Trans. Circuits Syst. Video Technol. 17, 1474–1484 (2007)
Kadaikar, A., Dauphin, G., Mokraoui, A.: Sequential block-based disparity map estimation algorithm for stereoscopic image coding. Signal Process. Image Commun. 39, 159–172 (2015)
Kadaikar, A., Dauphin, G., Mokraoui, A.: Joint disparity and variable size-block optimization algorithm for stereoscopic image compression. Signal Process. Image Commun. 61, 1–8 (2017)
Dauphin, G., Kaaniche, M., Mokraoui, A.: Block dependent dictionary based disparity compensation for stereo image coding. In: IEEE International Conference on Image Processing, ICIP, pp. 1–5. Québec City (Sept 2015)
Shen, G., Kim, W., Ortega, A., Lee, J., Wey, H.: Edge-aware intra prediction for depth-map coding. In: 2010 IEEE International Conference on Image Processing, pp. 3393–3396 (Sept 2010)
Chen, Y., Hannuksela, M.M., Zhu, L., Hallapuro, A., Gabbouj, M., Li, H.: Coding techniques in multiview video coding and joint multiview video model. In: 2009 Picture Coding Symposium, pp. 1–4 (May 2009)
Frajka, Tamás, Zeger, Kenneth: Residual image coding for stereo image compression. Opt. Eng. 42, 182–189 (2003)
Wallace, G.K.: The JPEG still picture compression standard. IEEE Trans. Consum. Electron. 38(1), 18–34 (1992)
Hachicha, W., Kaaniche, M., Beghdadi, A., Cheikh, F.A.: Efficient inter-view bit allocation methods for stereo image coding. IEEE Trans. Multimed. 17(6), 765–777 (2015)
Kadaikar, Aysha, Dauphin, Gabriel, Mokraoui, Anissa: Sequential block-based disparity map estimation algorithm for stereoscopic image coding. Signal Process. Image Commun. 39, 159–172 (2015)
Pan, R., Hou, Zh-X, Liu, Y.: Fast algorithms for inter-view prediction of multiview video coding. J. Multimed. 6, 191–201 (2011)
Kadri, I., Dauphin, G., Mokraoui, A.: Stereoscopic image coding performance using disparity-compensated block matching algorithm. In: IEEE International Conference on Signal Processing: Algorithms, Architectures, Arrangements, and Applications, SPA, pp. 1–5 (Sept 2019)
CCIT: Information Technology-Digital Compression and Coding of Continuous-Tone Still Images-Requirements and Guidelines. Technical Report T.81, The International Telegraph and Telephone Consultative Committee CCIT (Sept 1992)
Alam, L., Dhar, P.K., Hasan, M.R., Bhuyan, M.G., Daiyan, G.M.: An improved JPEG image compression algorithm by modifying luminance quantization table. Int. J. Comput. Sci. Netw. Secur. (IJCSNS) 17(1), 200–208 (2017)
Howard, Paul G., Vitter, Jeffrey: Arithmetic coding for data compression. Proc. IEEE 82, 857–865 (1994)
Kadaikar, A., Dauphin, G., Mokraoui, A.: Modified block matching algorithm improving rate-distortion performance for stereoscopic image coding. In: 2015 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), pp. 478–483 (Dec 2015)
Bjøntegaard, G.: Calculation of average PSNR differences between RD-curves. In: Document VCEG-M33, ITU-T VCEG Meeting, Austin, Texas, USA (2001)
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Kadri, I., Dauphin, G., Mokraoui, A. et al. Disparities selection controlled by the compensated image quality for a given bitrate. SIViP 14, 1143–1151 (2020). https://doi.org/10.1007/s11760-020-01643-1
- Stereoscopic image
- Disparity compensation
- Block matching algorithm