Abstract
3D holoscopic system can provide continuous motion parallax throughout the viewing zone with precise convergence and depth perception, for which it is regarded as a promising technique for future 3D TV. In this paper, a 3D holoscopic image coding scheme based on Gaussian mixture models (GMM) is introduced firstly, taking full advantage of the intrinsic characteristic of such particular type of content. Due to the shortcomings of GMM based method, an improved method is thereafter put forward, in which many parameters that are insignificant in the final estimator of GMM based method are avoided, and more surrounding pixels are used to obtain the model parameters with the help of the least square method. Experimental results indicate that the improved method can obtain considerable gains over HEVC intra prediction and several other prediction methods.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Sullivan, G.J., Ohm, J., 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)
Conti, C., Nunes, P., Soares, L.D.: New HEVC prediction modes for 3D holoscopic video coding. In: IEEE International Conference on Image Processing (ICIP), pp. 1325–1328 (2012)
Agooun, A., Fatah, O.A., Fernandez, J.C., Conti, C., Nunes, P., Soares, L.D.: Acquisition, processing and coding of 3D holoscopic content for immersive video systems. In: 3DTV-Conference: The True Vision Capture, Transmission and Display of 3D Video (3DTV-CON), pp. 1–4 (2013)
Lucas, L.F.R., Conti, C., Nunes, P., Soares, L.D., Rodrigues, N.M.M., Pagliari, C.L., da Silva, E.A.B., de Faria, S.M.M.: Locally linear embedding-based prediction for 3D holoscopic image coding using HEVC. In: 2014 Proceedings of the 22nd European Signal Processing Conference (EUSIPCO), pp. 11–15, 1–5 (2014)
Tan, T.K., Boon, C.S., Suzuki, Y.: Intra prediction by template matching. In: IEEE International Conference on Image Processing (ICIP), pp. 1693–1696 (2006)
Liu, D., An, P., Ma, R., Shen, L.: Disparity compensation based 3D holoscopic image coding using HEVC. In: 2015 IEEE China Summit and International Conference on Signal and Information Processing (ChinaSIP), pp. 201–205 (2015)
Li, Y., Sjostrom, M., Olsson, R., Jennehag, U.: Efficient intra prediction scheme for light field image compression. In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 539–543, 4–9 (2014)
Zhang, J., Ma, D.: Nonlinear prediction for Gaussian mixture image models. IEEE Trans. Image Process. 13(6), 836–847 (2004)
Yang, J., et al.: Video compressive sensing using Gaussian mixture models. IEEE Trans. Image Process. 23(11), 4863–4878 (2014)
Persson, D., Eriksson, T., Hedelin, P.: Packet video error concealment with Gaussian mixture models. IEEE Trans. Image Process. 17(2), 145–154 (2008)
Redner, A., Walker, H.F.: Mixture densities, maximum likelihood and the EM algorithm. SIAM Rev. 26, 195–239 (1984)
Bossen, F.: Common HM test conditions and soft-ware reference configurations, Document JCTVC-L1100 (2013)
Georgiev, T.: Jan 2013. http://www.tgeorgiev.net/
Acknowledgment
This work was supported in part by the National Natural Science Foundation of China, under Grants 61571285, U1301257, 61422111, and 61301112.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Liu, D., An, P., Du, T., Ma, R., Shen, L. (2017). An Improved 3D Holoscopic Image Coding Scheme Using HEVC Based on Gaussian Mixture Models. In: Yang, X., Zhai, G. (eds) Digital TV and Wireless Multimedia Communication. IFTC 2016. Communications in Computer and Information Science, vol 685. Springer, Singapore. https://doi.org/10.1007/978-981-10-4211-9_27
Download citation
DOI: https://doi.org/10.1007/978-981-10-4211-9_27
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-4210-2
Online ISBN: 978-981-10-4211-9
eBook Packages: Computer ScienceComputer Science (R0)