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Sensors 2015, 15(12), 30115-30125; doi:10.3390/s151229788

Low Complexity HEVC Encoder for Visual Sensor Networks

1
School of Computer and Software, Jiangsu Engineering Center of Network Monitoring, Nanjing University of Information Science and Technology, Nanjing 210044, China
2
School of Computer Science and Engineering, Hebei University of Technology, Tianjin 300401, China
*
Author to whom correspondence should be addressed.
Academic Editor: Leonhard M. Reindl
Received: 26 October 2015 / Revised: 24 November 2015 / Accepted: 26 November 2015 / Published: 2 December 2015
(This article belongs to the Section Sensor Networks)
View Full-Text   |   Download PDF [786 KB, uploaded 2 December 2015]   |  

Abstract

Visual sensor networks (VSNs) can be widely applied in security surveillance, environmental monitoring, smart rooms, etc. However, with the increased number of camera nodes in VSNs, the volume of the visual information data increases significantly, which becomes a challenge for storage, processing and transmitting the visual data. The state-of-the-art video compression standard, high efficiency video coding (HEVC), can effectively compress the raw visual data, while the higher compression rate comes at the cost of heavy computational complexity. Hence, reducing the encoding complexity becomes vital for the HEVC encoder to be used in VSNs. In this paper, we propose a fast coding unit (CU) depth decision method to reduce the encoding complexity of the HEVC encoder for VSNs. Firstly, the content property of the CU is analyzed. Then, an early CU depth decision method and a low complexity distortion calculation method are proposed for the CUs with homogenous content. Experimental results show that the proposed method achieves 71.91% on average encoding time savings for the HEVC encoder for VSNs. View Full-Text
Keywords: visual sensor networks; video compression; HEVC; coding unit; low complexity visual sensor networks; video compression; HEVC; coding unit; low complexity
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Pan, Z.; Chen, L.; Sun, X. Low Complexity HEVC Encoder for Visual Sensor Networks. Sensors 2015, 15, 30115-30125.

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