Abstract-Determining the best partitioning structure of a Coding Tree Unit (CTU) is one of the most time consuming operations in HEVC encoding. Specifically, it is the evaluation of the quadtree hierarchy using the Rate-Distortion (RD) optimization that has the most significant impact on the encoding time, especially in the cases of High Definition (HD) and Ultra High Definition (UHD) videos. In order to expedite the encoding for low delay applications, this paper proposes a Coding Unit (CU) size selection and encoding algorithm for inter-prediction in the HEVC. To this end, it describes (i) two CU classification models based on Inter N×N mode motion features and RD cost thresholds to predict the CU split decision, (ii) an online training scheme for dynamic content adaptation, (iii) a motion vector reuse mechanism to expedite the motion estimation process, and finally introduces (iv) a computational complexity to coding efficiency trade-off process to enable flexible control of the algorithm. The experimental results reveal that the proposed algorithm achieves a consistent average encoding time performance ranging from 55% -58% and 57% -61% with average Bjøntegaard Delta Bit Rate (BDBR) increases of 1.93% -2.26% and 2.14% -2.33% compared to the HEVC 16.0 reference software for the low delay P and low delay B configurations, respectively, across a wide range of content types and bit rates.

Abstract-The energy consumption of Consumer Electronic (CE) devices during media playback is inexorably linked to the computational complexity of decoding compressed video. Reducing a CE device's the energy consumption is therefore becoming ever more challenging with the increasing video resolutions and the complexity of the video coding algorithms. To this end, this paper proposes a framework that alters the video bit stream to reduce the decoding complexity and simultaneously limits the impact on the coding efficiency. In this context, this paper (i) first performs an analysis to determine the trade-off between the decoding complexity, video quality and bit rate with respect to a reference decoder implementation on a General Purpose Processor (GPP) architecture. Thereafter, (ii) a novel generic decoding complexity-aware video coding algorithm is proposed to generate decoding complexity-rate-distortion optimized High Efficiency Video Coding (HEVC) bit streams. The experimental results reveal that the bit streams generated by the proposed algorithm achieve 29.43% and 13.22% decoding complexity reductions for a similar video quality with minimal coding efficiency impact compared to the state-of-the-art approaches when applied to the HM16.0 and openHEVC decoder implementations, respectively. In addition, analysis of the energy consumption behavior for the same scenarios reveal up to 20% energy consumption reductions while achieving a similar video quality to that of HM 16.0 encoded HEVC bit streams.

The complexity of the novel video compression algorithms is a major contributor for the increased demand of processing and energy resources for video playback in consumer electronic devices. Therefore, a decoder complexity reduction mechanism is proposed which constitutes a model that predicts the decoder's complexity requirements to decode the HEVC encoded bit streams with a 4.2% average prediction error and a decoder complexity optimized encoding algorithm, which reduces the decoding complexity by an average of 28.06% and 41.19% with a-1.91 dB and-2.46 dB impact to the BD-PSNR for the low delay P and random access configurations, respectively.

Determining the best partitioning structure for a given Coding Tree Unit (CTU) is one of the most time consuming operations within the HEVC encoder. The brute force search through quadtree hierarchy has a significant impact on the encoding time of high definition (HD) videos. This paper presents a fast coding unit size decision-taking algorithm for intra prediction in HEVC. The proposed algorithm utilizes a low complex texture analysis technique based on the local range property of a pixel in a given neighborhood. Simulation results show that the proposed algorithm achieves an average of 72.24% encoding time efficiency improvement with similar rate distortion performance compared to HEVC reference software HM12.0 for HD videos.

The rising demand for media consumption via mobile devices and the emergence of complex video coding algorithms present an additional challenge for the energy management algorithms in resourceconstrained consumer electronic devices. Thus, generating energyoptimized video bit streams will positively contribute towards overcoming this challenge. This paper introduces a novel energy model for intra-frame decoding of HEVC encoded video that predicts the decoding energy of a coding unit. Thereafter, a novel energy-ratedistortion optimized coding mode selection algorithm is proposed to generate energy-efficient bit streams using the proposed energy model within the encoder. The proposed energy model is shown to predict the decoding energy of a coding unit with an average error less than 2%. Moreover, the proposed coding mode selection algorithm achieves an average 10.8% reduction in the energy consumed at the decoder with a-0.25 dB impact to the Bjøntegaard Delta-Peak Signal-to-Noise Ratio.