Rate Selection Algorithm of DASH Client Based on Contrast Sensitivity

ZHANG Xinyou; WANG Yuanxun; XING Huanlai; WANG Honggang

doi:10.11999/JEIT160150

Volume 38 Issue 11

Dec. 2016

Turn off MathJax

Article Contents

Article Navigation > Journal of Electronics & Information Technology > 2016 > 38(11): 2826-2831

ZHANG Xinyou, WANG Yuanxun, XING Huanlai, WANG Honggang. Rate Selection Algorithm of DASH Client Based on Contrast Sensitivity[J]. Journal of Electronics & Information Technology, 2016, 38(11): 2826-2831. doi: 10.11999/JEIT160150

Citation:

ZHANG Xinyou, WANG Yuanxun, XING Huanlai, WANG Honggang. Rate Selection Algorithm of DASH Client Based on Contrast Sensitivity[J]. Journal of Electronics & Information Technology, 2016, 38(11): 2826-2831. doi: 10.11999/JEIT160150

Citation:

PDF( 417 KB)

Rate Selection Algorithm of DASH Client Based on Contrast Sensitivity

doi: 10.11999/JEIT160150

1.
(School of Information Science and Technology, Southwest Jiaotong University, Chengdu 611756, China)
2.
(ECE Department, University of Massachusetts, Dartmouth, MA 02747, USA)

Funds:

The National Natural Science Foundation of China (61401374)

Received Date: 2016-02-02
Rev Recd Date: 2016-07-29
Publish Date: 2016-11-19

Abstract

Abstract

One significant advantage of rate selection algorithms based on bandwidth estimation is the high bandwidth utilization rate. They are, however, vulnerable to network bandwidth fluctuations, leading to appearance of rate instantaneous peak value and hence wasting unnecessary bandwidth consumption. To tackle the problem above, this paper proposes a novel rate selection algorithm based on the contrast sensitivity of human eyes, where in the client eyes cutoff spatial frequency under the current viewing conditions is calculated by using the human contrast sensitivity model. The algorithm selects the rate of video fragment which has the minimum absolute difference value to the spatial frequency computed, stored in server as the target rate. Compared with those methods for calculating the target rate based on bandwidth estimation and testing target rate in different angles, the proposed method gets the ladder diagrams of rate calculation of both methods. Experimental results demonstrate that the proposed algorithm is able to save a considerable amount of bandwidth without the loss of video quality, with viewing angle from 5 to 15.
- Contrast sensitivity,
- Cutoff spatial frequency,
- Dynamic Adaptive Streaming over Http (DASH),
- Rate selection

FullText(HTML)

References(19)

References

LUCA De Cicco and SAVERIO Mascolo. An adaptive video streaming control system: Modeling, validation and performance evaluation[J]. IEEE/ACM Transactions on Networking, 2013, 22(2): 526-539. doi: 10.1109/TNET.2013. 2253797.

SAAMER A, NARAYaANASWAMY S, BEGEN A C, et al. An experimental evaluation of rate-adaptive video players over [U5]HTTP[J]. Signal Processing: Image Communication, 2012, 27(4): 271-287. doi: 10.1016/j.image.2011.10.003.

RAN Yongyi, SHI Youkang, YANG Enzhong, et al. Dynamic resource allocation for video transcoding with QoS guaranteeing in cloud-based DASH system[C]. IEEE GlobeCom Workshops, (GC Wkshps), Austin, 2014: 144-149.

TIAN Guibin and LIU Yong. Towards agile and smooth video adaptation in dynamic HTTP streaming[J]. IEEE/ACM Transactions on Networking, 2015, 9(11): 1-14. doi:[U6] 10.1109/ TNET.2015.2464700.

REZNIK Y A. User-adaptive mobile video streaming using MPEG-DASH[C]. SPIE Optical Engineering+Applications. International Society for Optics and Photonics, San Diego, 2013: 88560J-88560J-5.

VANAM R and REZNIK Y A. Perceptual pre-processing filter for user-adaptive coding and delivery of visual information[C]. IEEE Picture Coding Symposium (PCS), San Jose, 2013: 426-429.

VANAM R, KEROFAKY L J, and REZNIK Y A. Perceptual pre-processing filter for adaptive video on demand content delivery[C]. IEEE International Conference on Image Processing (ICIP), Paris, 2014: 2537-2541.

CHEN Wei, MA Liangping, STERNBERG G, et al. User-aware DASH over Wi-Fi[C]. International Conference on Computing, Networking and Communications (ICNC), Garden Grove, 2015: 749-753.

KEROFAKY L, VANAM R, and REZNIK Y. Adapting objective video quality metrics to ambient lighting[C]. Seventh International Workshop on Quality of Multimedia Experience (QoMEX), Pylos-Nestoras, 2015: 1-6.

NILL N B. A visual model weighted cosine transform for image compression and quality assessment[J]. IEEE Transactions on Communications, 1985, 33(6): 551-557. doi: 10.1109/TCOM. 985.1096337.

SCHULZE T J. Procedure for calculating the resolution of electro-optical systems[C]. International Society for Optics and Photonics, San Diego-DL Tentative, 1990: 317-327.

WU Yiyan and COLL D C. Multilevel block truncation coding using a minimax error criterion for high-fidelity compression of digital images[J]. IEEE Transactions on Communications, 1993, 41(8): 1179-1191. doi: 10.1109/26. 231961.

DALY S J. Visible differences predictor: an algorithm for the assessment of image fidelity[C]. SPIE/IST 1992 Symposium on Electronic Imaging: Science and Technology, Cambridge, MA, 1992: 2-15.

BARTEN P G J. Formula for the contrast sensitivity of the human eye[J]. Proceedings of SPIE - The International Society for Optical Engineering, 2003, 5294: 231-238. doi: 10.1117/12. 537476.

REZNIK Y A and VANAM R. Improving coding and delivery of video by exploiting the oblique effect[C]. IEEE Global Conference on Signal and Information Processing (GlobalSIP), Austin, 2013: 775-778.

The SVT high definition multi format test set[EB/OL]. ftp://vqeg.its.bldrdoc.gov/HDTV/SVT Multiformat/.2006. 2.

MUELLER C, LEDERER S, POECHER J, et al. Demo paper: Libdash-an open source software library for the mpeg-dash standard[C]. IEEE International Conference on Multimedia and Expo Workshops (ICMEW), San Jose, 2013: 1-2.

THANG T C, HO Q D, KANG J W, et al. Adaptive streaming of audiovisual content using MPEG DASH[J]. IEEE Transactions on Consumer Electronics, 2012, 58(1): 78-85. doi: 10.1109/ TCE.2012.6170058.

SEYEDEBRAHIMI M, PENG Xiaohong, and BAILEY C. Client QoE-oriented segment selection for DASH[C]. IEEE International Conference on Computer and Information Technology, Liverpool, 2015: 1663-1668.

Relative Articles

Supplements(0)

Cited By

Proportional views