Fast Video Encoding Algorithm for the Internet of Things Environment Based on High Efficiency Video Coding

Jong-Hyeok Lee, Kyung-Soon Jang, Byung-Gyu Kim, Seyoon Jeong and Jin Soo Choi

International Journal of Distributed Sensor Networks, 2015, vol. 11, issue 11, 146067

Abstract: Video data for the Internet traffic is increasing, and video data transmission is important for consideration of real-time process in the Internet of Things (IoT). Thus, in the IoT environment, video applications will be valuable approach in networks of smart sensor devices. High Efficiency Video Coding (HEVC) has been developed by the Joint Collaborative Team on Video Coding (JCT-VC) as a new generation video coding standard. Recently, HEVC includes range extensions (RExt), scalable coding extensions, and multiview extensions. HEVC RExt provides high resolution video with a high bit-depth and an abundance of color formats. In this paper, a fast intraprediction unit decision method is proposed to reduce the computational complexity of the HEVC RExt encoder. To design intramode decision algorithm, Local Binary Pattern (LBP) of the current prediction unit is used as texture feature. Experimental results show that the encoding complexity can be reduced by up to 12.35% on average in the AI-Main profile configuration with only a small bit-rate increment and a PSNR decrement, compared with HEVC test model (HM) 12.0-RExt4.0 reference software.

Date: 2015
References: Add references at CitEc
Citations:

Downloads: (external link)
https://journals.sagepub.com/doi/10.1155/2015/146067 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:11:y:2015:i:11:p:146067

DOI: 10.1155/2015/146067

Access Statistics for this article

More articles in International Journal of Distributed Sensor Networks
Bibliographic data for series maintained by SAGE Publications ().