The Alliance for Open Media (AOMedia) aims at generating a new, royalty-free video codec specification named AV1 that is scheduled for completion in the 2nd half of 2017. To facilitate AV1 market acceptance and rapid deployment, attention has been paid toward development of hardware friendly coding tools. This paper presents the following techniques to facilitate hardware implementation of AV1 inter prediction: 1) a simplified motion vector prediction scheme to reduce memory footprint / bandwidth; 2) methods to limit / remove the dependency between the computation of probability context model and the reconstruction of motion vectors to improve hardware throughput. Experimental results on a wide range of test clips show negligible quality impact for 1) and minor quality impact for 2) while the motion vectors line buffer memory footprint is reduced by 50%, motion vectors local memory is reduced by 33%, and the throughput of the arithmetic decoder remains unchanged.

In this paper, we propose a cross-layer optimization scheme for multi-user video streaming over the uplink of IEEE 802.11e HCCA wireless network. The objective is to minimize the energy consumption of all users, including both video encoder energy and wireless transmission energy, while delivering desired video quality for each user. In our proposed scheme, both cross-layer optimization of individual mobile terminal and inter-user resource allocation are carried out, so that the video encoder and wireless transmitter configurations can be jointly steered. Experimental results show that when compared to the transmission system without cross-layer optimization, our proposed scheme is able to reduce total energy consumption from 35% up to 80%, while satisfying the same video quality target.

We consider the problem of packet scheduling for the transmission of multiple video streams over a wireless local area network (WLAN). A cross-layer optimization framework is proposed to minimize the wireless transceiver energy consumption while reaching the user required visual quality. The framework relies on the IEEE 802.11 standard and on a wavelet-based scalable video coding scheme. It extends our previous work on energy-efficient scheduling by introducing an application-level video quality metric as QoS constraint (instead of a quality metric at the level of the communication layers) and by reformulating the energy minimization problem subject to the QoS constraint in order to also consider the fairness among users. Simulation results demonstrate significant additional energy gains by means of these extensions.

In wireless video streaming, it is desirable to minimize the energy consumption of mobile devices while achieving target video quality. For this purpose, it is essential to model (i.e., estimate) the energy cost of the streaming system, including both video encoder and wireless transmission energy, under different system settings. In this paper, an energy consumption model is proposed for a MPEG-4 simple profile encoder implemented in ASIC. Our proposed model consists of three major steps: 1) compute the encoder energy consumption through power simulations; 2) empirically model the impact of configuration parameters through curve fitting; and 3) online updating of model coefficients. Experimental results show that our proposed model works well for different types of video, and the average estimation error is below 6%.

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The rapid growth of mobile communications and the widespread access to information via the Internet have resulted in a strong demand for robust transmission of compressed image and video data for various multimedia applications and services. The challenge of robust transmission is to protect the compressed image/video data against hostile channel conditions while bringing little impact on bandwidth efficiency. This paper addresses this critical problem and provides an overview of the error-resilient approaches that have been evaluated and inserted into the emerging JPEG-2000 wavelet-based image coding standard. We also review the state-of-the-art techniques adopted in the MPEG-4 standard for robust transmission of video and still texture data. These techniques include resynchronization strategies, data partitioning, reversible VLCs, and header extension codes. The performance of these approaches under various channel conditions is evaluated.

In this paper, we propose a bit-stream packetization approach to make the MPEG-4 still texture bit-stream robust to channel degradation. Our approach does not affect the spatial/quality scalability features of the still texture algorithm, and it has limited effect on coding efficiency. Also, this packetization approach requires minimal changes to the syntax and a small overhead. Finally, the proposed technique is shown to provide good error robustness over a wide range of error conditions.

In this paper we present a coding scheme for color images aiming at high compression ratios. It is based on perceptually classified vector quantization (VQ), where the different classes are chosen to achieve a better quality of the decoded image. Spatial correlation is reduced by a tree structured wavelet decomposition, then prediction of the insignificant coefficients is performed across subbands. Afterwards, the reduced set of data is organized in vectors in such a way that residual intra and inter band correlation are exploited. Finally, such vectors are coded by a classified VQ. Reconstructed images with good quality and a compression ratio higher that 100:1 have been produced by the proposed scheme, which has been shown to outperform the JPEG standard.

Block matching motion estimation techniques have shown their efficiency to reduce the temporal redundancy for video coding. However, they tend to introduce annoying block artifacts in the displaced frame difference due to their block-based model. In this paper, we propose a motion field refinement technique in order to overcome these artifacts. The method relies on vector quantization. The patterns to segment the motion field are derived by the LBG algorithm, the training being performed on segmented patterns obtained from natural images. Simulation results show a significant improvement due to the proposed method, in particular moving edges are much better motion compensated and the visual quality is greatly enhanced.>