Survey of Error Concealment techniques: Research directions and open issues

© 2015 IEEE. Error Concealment (EC) techniques use either spatial, temporal or a combination of both types of information to recover the data lost in transmitted video. In this paper, existing EC techniques are reviewed, which are divided into three categories, namely Intra-frame EC, Inter-frame EC, and Hybrid EC techniques. We first focus on the EC techniques developed for the H.264/AVC standard. The advantages and disadvantages of these EC techniques are summarized with respect to the features in H.264. Then, the EC algorithms are also analyzed. These EC algorithms have been recently adopted in the newly introduced H.265/HEVC standard. A performance comparison between the classic EC techniques developed for H.264 and H.265 is performed in terms of the average PSNR. Lastly, open issues in the EC domain are addressed for future research consideration

Frame Interpolation for Cloud-Based Mobile Video Streaming

© 2016 IEEE. Cloud-based High Definition (HD) video streaming is becoming popular day by day. On one hand, it is important for both end users and large storage servers to store their huge amount of data at different locations and servers. On the other hand, it is becoming a big challenge for network service providers to provide reliable connectivity to the network users. There have been many studies over cloud-based video streaming for Quality of Experience (QoE) for services like YouTube. Packet losses and bit errors are very common in transmission networks, which affect the user feedback over cloud-based media services. To cover up packet losses and bit errors, Error Concealment (EC) techniques are usually applied at the decoder/receiver side to estimate the lost information. This paper proposes a time-efficient and quality-oriented EC method. The proposed method considers H.265/HEVC based intra-encoded videos for the estimation of whole intra-frame loss. The main emphasis in the proposed approach is the recovery of Motion Vectors (MVs) of a lost frame in real-time. To boost-up the search process for the lost MVs, a bigger block size and searching in parallel are both considered. The simulation results clearly show that our proposed method outperforms the traditional Block Matching Algorithm (BMA) by approximately 2.5 dB and Frame Copy (FC) by up to 12 dB at a packet loss rate of 1%, 3%, and 5% with different Quantization Parameters (QPs). The computational time of the proposed approach outperforms the BMA by approximately 1788 seconds

QoE Enhancement for Stereoscopic 3DVideo Quality Based on Depth and Color Transmission over IP Networks: A Review

In this review paper we focus on the enhancement of Quality of Experience (QoE) for stereoscopic 3D video based on depth information. We focus on stereoscopic video format because it takes less bandwidth than other format when 3D video is transmitted over an error channel but it is easily affected by the network parameters such as packets loss, delay and jitter. The packet loss on 3D video has more impact in the depth information than other 3D video factors such as comfort, motion, disparity and discomfort. The packet loss on depth information causes undesired effect on color and depth maps. Therefore, in order to minimize quality degradation, the application of frame loss concealment technique is preferred. This technique is expected to improve the QoE for end users. In this paper we will also review 3D video factors and their challenges, methods of measuring the QOE, algorithms used for packets loss recovery.

Error-resilient multi-view video plus depth based 3-D video coding

Three Dimensional (3-D) video, by definition, is a collection of signals that can provide depth perception of a 3-D scene. With the development of 3-D display technologies and interactive multimedia systems, 3-D video has attracted significant interest from both industries and academia with a variety of applications. In order to provide desired services in various 3-D video applications, the multiview video plus depth (MVD) representation, which can facilitate the generation of virtual views, has been determined to be the best format for 3-D video data. Similar to 2-D video, compressed 3-D video is highly sensitive to transmission errors due to errors propagated from the current frame to the future predicted frames. Moreover, since the virtual views required for auto-stereoscopic displays are rendered from the compressed texture videos and depth maps, transmission errors of the distorted texture videos and depth maps can be further propagated to the virtual views. Besides, the distortions in texture and depth show different effects on the rendering views. Therefore, compared to the reliability of the transmission of the 2-D video, error-resilient texture video and depth map coding are facing major new challenges. This research concentrates on improving the error resilience performance of MVD-based 3-D video in packet loss scenarios. Based on the analysis of the propagating behaviour of transmission errors, a Wyner-Ziv (WZ)-based error-resilient algorithm is first designed for coding of the multi-view video data or depth data. In this scheme, an auxiliary redundant stream encoded according to WZ principle is employed to protect a primary stream encoded with standard multi-view video coding codec. Then, considering the fact that different combinations of texture and depth coding mode will exhibit varying robustness to transmission errors, a rate-distortion optimized mode switching scheme is proposed to strike the optimal trade-off between robustness and compression effciency. In this approach, the texture and depth modes are jointly optimized by minimizing the overall distortion of both the coded and synthesized views subject to a given bit rate. Finally, this study extends the research on the reliable transmission of view synthesis prediction (VSP)-based 3-D video. In order to mitigate the prediction position error caused by packet losses in the depth map, a novel disparity vector correction algorithm is developed, where the corrected disparity vector is calculated from the depth error. To facilitate decoder error concealment, the depth error is recursively estimated at the decoder. The contributions of this dissertation are multifold. First, the proposed WZbased error-resilient algorithm can accurately characterize the effect of transmission error on multi-view distortion at the transform domain in consideration of both temporal and inter-view error propagation, and based on the estimated distortion, this algorithm can perform optimal WZ bit allocation at the encoder through explicitly developing a sophisticated rate allocation strategy. This proposed algorithm is able to provide a finer granularity in performing rate adaptivity and unequal error protection for multi-view data, not only at the frame level, but also at the bit-plane level. Secondly, in the proposed mode switching scheme, a new analytic model is formulated to optimally estimate the view synthesis distortion due to packet losses, in which the compound impact of the transmission distortions of both the texture video and the depth map on the quality of the synthesized view is mathematically analysed. The accuracy of this view synthesis distortion model is demonstrated via simulation results and, further, the estimated distortion is integrated into a rate-distortion framework for optimal mode switching to achieve substantial performance gains over state-of-the-art algorithms. Last, but not least, this dissertation provides a preliminary investigation of VSP-based 3-D video over unreliable channel. In the proposed disparity vector correction algorithm, the pixel-level depth map error can be precisely estimated at the decoder without the deterministic knowledge of the error-free reconstructed depth. The approximation of the innovation term involved in depth error estimation is proved theoretically. This algorithm is very useful to conceal the position-erroneous pixels whose disparity vectors are correctly received