Fast Mode Assignment for Quality Scalable Extension of the High Efficiency Video Coding (HEVC) Standard: A Bayesian Approach

ABSTRACT The new compression standard, known as the High Efficiency Video Coding (HEVC), aims at significantly improving the compression efficiency compared to previous standards. There has been significant interest in developing a scalable version of this standard. As expected, the HEVC scalable video version, which is called SHVC, increases the complexity of the codec compared to the non-scalable counterpart. In this paper, we propose an adaptive fast mode assigning method based on a Bayesian classifier that reduces SHVC's coding complexity by up to 68.55%, while maintaining the overall quality and bit-rates

AN H.264-BASED VIDEO ENCODING SCHEME FOR 3D TV

This paper presents an H.264-based scheme for compress-ing 3D content captured by 3D depth range cameras. Exist-ing MPEG-2 based schemes take advantage of the correla-tion between the 2D video sequence and its corresponding depth map sequence, and use the 2D motion vectors (MV) for the depth video sequence as well. This improves the speed of encoding the depth map sequence, but it results in an increase in the bitrate or a drop in the quality of the re-constructed 3D video. This is found to be due to the MVs of the 2D video sequence not being the best choice for encod-ing some parts of the depth map sequence containing sharp edges or corresponding to distant objects. To solve this problem, we propose an H.264-based method which re-estimates the MVs and re-selects the appropriate modes for these regions. Experimental results show that the proposed method enhances the quality of the encoded depth map se-quence by an average of 1.77 dB. Finding the MVs of the sharp edge-included regions of the depth map sequence amounts to 30.64 % of the computational effort needed to calculate MVs for the whole depth map sequence. 1

Perceptual quality-driven resource allocation in energy-aware wireless video multicasting

© 2014 ICST.In conjunction with the rising trend towards consumption of resource-hungry multimedia content over wireless medium, efficient radio resource allocation (eRRA) represents an ongoing challenge to network operators. This paper explores the application of multicasting in light of an eRRA that considers the perceptual quality aspect of wireless video transmission such that transmission energy is minimized. A multiuser orthogonal frequency-division multiplexing (OFDM) environment is considered. The resource allocation scheme presented is based on the genetic algorithm (GA) and offers fairness through the balance of average perceptual quality and minimal total energy among all subscribers in multicasting groups. In order to assist with this balance, a utility function is introduced as a fitness function for the GA. The allocation scheme relies on a well-established video quality model (VQM) for assessment of user-perceived quality. Simulation results show that the allocation scheme helps to preserve the energy requirement at low levels despite the proportionate rise in the number of subscribers. Moreover, perceived quality is well-secured and maintained at high levels, with a consistent increase of the utility value. Reflecting on today's consumption patterns of popular video content, adoption of the presented scheme in multicasting would help lessen the carbon footprint emitted by wireless communications, while consumers' quality of experience (QoE) is maintained

Perceptual quality-driven resource allocation in energy-aware wireless video multicasting

© 2014 ICST.In conjunction with the rising trend towards consumption of resource-hungry multimedia content over wireless medium, efficient radio resource allocation (eRRA) represents an ongoing challenge to network operators. This paper explores the application of multicasting in light of an eRRA that considers the perceptual quality aspect of wireless video transmission such that transmission energy is minimized. A multiuser orthogonal frequency-division multiplexing (OFDM) environment is considered. The resource allocation scheme presented is based on the genetic algorithm (GA) and offers fairness through the balance of average perceptual quality and minimal total energy among all subscribers in multicasting groups. In order to assist with this balance, a utility function is introduced as a fitness function for the GA. The allocation scheme relies on a well-established video quality model (VQM) for assessment of user-perceived quality. Simulation results show that the allocation scheme helps to preserve the energy requirement at low levels despite the proportionate rise in the number of subscribers. Moreover, perceived quality is well-secured and maintained at high levels, with a consistent increase of the utility value. Reflecting on today's consumption patterns of popular video content, adoption of the presented scheme in multicasting would help lessen the carbon footprint emitted by wireless communications, while consumers' quality of experience (QoE) is maintained

QoE Aware Resource Allocation for Video Communications over LTE Based Mobile Networks

As the limits of video compression and usable wireless radio resources are exhausted, providing increased protection to critical data is regarded as a way forward to increase the effective capacity for delivering video data. This paper explores the provisioning of selective protection in the physical layer to critical video data and evaluates its effectiveness when transmitted through a wireless multipath fading channel. In this paper, the transmission of HEVC encoded video through an LTE-A wireless channel is considered. HEVC encoded video data is ranked based on how often each area of the picture is referenced by subsequent frames within a GOP in the sequence. The critical video data is allotted to the most robust OFDM resource blocks (RBs), which are the radio resources in the time-frequency domain of the LTE-A physical layer, to provide superior protection. The RBs are ranked based on a prediction for their robustness against noise. Simulation results show that the proposed content aware resource allocation scheme helps to improve the objective video quality up to 37dB at lower channel SNR levels when compared against the reference system, which treats video data uniformly. Alternatively, with the proposed technique the transmitted signal power can be lowered by 30% without sacrificing video quality at the receiver

A Study on the HEVC Performance Over Lossy Networks

Abstract-The high level of compression achieved by HEVC raises a question regarding its error-resilience performance extremely compressed data over an imperfect medium. In this paper, we study the behavior of this newly developed video coding standard over diverse networking scenarios. It is shown that HEVC is less error resilient compared to H.264/AVC, especially in the scenes with high amount of motion, in exchange of a significantly reduced bandwidth