The encoding of HD videos faces two challenges: requirements for a strong processing power and a large storage space. One time-efficient solution addressing these challenges is to use a cloud platform and to use a scalable video coding technique to generate multiple video streams with varying bit-rates. Packet-loss is very common during the transmission of these video streams over the Internet and becomes another challenge. One solution to address this challenge is to retransmit lost video packets, but this will create end-to-end delay. Therefore, it would be good if the problem of packet-loss can be dealt with at the user's side. In this paper, we present a novel system that encodes and stores the videos using the Amazon cloud computing platform, and recover lost video frames on user side using a new Error Concealment (EC) technique. To efficiently utilize the computation power of a user's mobile device, the EC is performed based on a multiple-thread and parallel process. The simulation results clearly show that, on average, our proposed EC technique outperforms the traditional Block Matching Algorithm (BMA) and the Frame Copy (FC) techniques.

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.

Phase unwrapping is used to get absolute phase from the wrapped phase image and remove 2π discontinuities. It is computational extensive process. It requires a lot of iterations, first in one dimension of the image and then in the other dimension, to unwrap the phase. The primary limitation of the phase unwrapping is that it is a path dependant process which can only be executed sequentially. In this paper we have developed a new method for the parallel processing of path dependant phase unwrapping. In this proposed method different blocks of image are executed parallely by separate threads independent of each other. The algorithm used in this paper is Itoh for phase unwrapping. The results achieved by parallel processing of phase unwrapping are 99% better as compared to the sequential processing.

Conventional video compression relies on interframe prediction (motion estimation), intra frame prediction and variable-length entropy encoding to achieve high compression ratios but, as a consequence, produces an encoded bitstream that is inherently sensitive to channel errors. In order to ensure reliable delivery over lossy channels, it is necessary to invoke various additional error detection and correction methods. In contrast, techniques such as Pyramid Vector Quantisation have the ability to prevent error propagation through the use of fixed length codewords. This paper introduces an efficient rate distortion optimisation algorithm for intra-mode PVQ which offers similar compression performance to intra H.264/AVC and Motion JPEG 2000 while offering inherent error resilience. The performance of our enhanced codec is evaluated for HD content in the context of a realistic (IEEE 802.11n) wireless environment. We show that PVQ provides high tolerance to corrupted data compared to the state of the art while obviating the need for complex encoding tools.

Video encoders such as H.264 and VC-1 rely on variable length coding, motion estimation and intra prediction to achieve high compression ratios but, as a consequence, produce an encoded bitstream that is extremely sensitive to channel errors. Pyramid Vector Quantisation, which generates fixed length codes, has been shown to provide excellent error resilience for wireless transmission of HD video. This paper presents an efficient rate distortion optimisation algorithm for PVQ which yields impressive intra coding performance with low complexity. The compression performance of PVQ is comparable with intra-H.264 and intra-VC-1. The error resilience of PVQ is also compared with H.264 and VC-1 in a representative MIMO Wireless LAN environment, showing the superior performance of PVQ.

This paper explores rules and defines cross layer parameters that enhance the received video quality per unit bandwidth while observing strict video QoS for unicast video transmission over mobile WiMAX. Channel capacity and goodput are estimated using a detailed MAC/PHY simulator. The simulator supports link adaptation of the PHY layer Modulation and Coding Scheme (MCS) alongside MAC layer Automatic Repeat Request (ARQ). A new performance indicator, PSNR per Hz, is defined to capture the video PSNR attained for a given effective bandwidth. For the 3GPP urban micro channel, MCS and MAC layer block lifetime are jointly determined as a function of average channel SNR in order to enhance video PSNR and goodput. At low SNR higher level QAM is inefficient (as a result of excessive MAC layer ARQ or high packet error rate) for video transfer. Results show that video efficiency improves for block lifetimes up to 100ms, since the greater use of ARQ enables more spectrally efficient MCS modes to be applied.

Video Source encoders such as H.264 and VC-1 are in common use today and provide impressive compression performance. These use variable length coding and predictive coding to achieve high compression ratios but as a consequence render the encoded bitstream extremely sensitive to channel errors. In this paper we revisit an alternative technique, Pyramid Vector Quantisation, which generates fixed length codes. Intra mode PVQ is presented as a means of robustly compressing and wirelessly transmitting HD Video. The paper shows that PVQ is an effective codec for indoor wireless transmission of HD video. Comparing the required channel SNR for an H.264 based system with a PVQ based system shows that PVQ can operate at a much lower SNR (with gains of up to 11 dB) while still providing excellent video quality and compression performance.