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Journal Article Fast Video Encoding Algorithm for the Internet of Things Environment Based on High Efficiency Video Coding
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Authors
Jong-Hyeok Lee, Kyung-Soon Jang, Byung-Gyu Kim, Seyoon Jeong, Jin Soo Choi
Issue Date
2015-11
Citation
International Journal of Distributed Sensor Networks, v.2015, pp.1-11
ISSN
1550-1329
Publisher
Hindawi Publishing
Language
English
Type
Journal Article
DOI
https://dx.doi.org/10.1155/2015/146067
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.
KSP Keywords
Bit rate, Computational complexity, Current Prediction, Data transmission, Decision algorithm, Encoding algorithm, HEVC Test Model(HM), High Efficiency Video coding(HEVC), High resolution video, Internet traffic, IoT environment
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