Intra Coding Strategy for Video Error Resiliency: Behavioral Analysis

One challenge in video transmission is to deal with packet loss. Since the compressed video streams are sensitive to data loss, the error resiliency of the encoded video becomes important. When video data is lost and retransmission is not possible, the missed data should be concealed. But loss concealment causes distortion in the lossy frame which also propagates into the next frames even if their data are received correctly. One promising solution to mitigate this error propagation is intra coding. There are three approaches for intra coding: intra coding of a number of blocks selected randomly or regularly, intra coding of some specific blocks selected by an appropriate cost function, or intra coding of a whole frame. But Intra coding reduces the compression ratio; therefore, there exists a trade-off between bitrate and error resiliency achieved by intra coding. In this paper, we study and show the best strategy for getting the best rate-distortion performance. Considering the error propagation, an objective function is formulated, and with some approximations, this objective function is simplified and solved. The solution demonstrates that periodical I-frame coding is preferred over coding only a number of blocks as intra mode in P-frames. Through examination of various test sequences, it is shown that the best intra frame period depends on the coding bitrate as well as the packet loss rate. We then propose a scheme to estimate this period from curve fitting of the experimental results, and show that our proposed scheme outperforms other methods of intra coding especially for higher loss rates and coding bitrates

Digital recording of performing arts: formats and conversion

B

Image and Video Coding/Transcoding: A Rate Distortion Approach

Due to the lossy nature of image/video compression and the expensive bandwidth and computation resources in a multimedia system, one of the key design issues for image and video coding/transcoding is to optimize trade-off among distortion, rate, and/or complexity. This thesis studies the application of rate distortion (RD) optimization approaches to image and video coding/transcoding for exploring the best RD performance of a video codec compatible to the newest video coding standard H.264 and for designing computationally efficient down-sampling algorithms with high visual fidelity in the discrete Cosine transform (DCT) domain. RD optimization for video coding in this thesis considers two objectives, i.e., to achieve the best encoding efficiency in terms of minimizing the actual RD cost and to maintain decoding compatibility with the newest video coding standard H.264. By the actual RD cost, we mean a cost based on the final reconstruction error and the entire coding rate. Specifically, an operational RD method is proposed based on a soft decision quantization (SDQ) mechanism, which has its root in a fundamental RD theoretic study on fixed-slope lossy data compression. Using SDQ instead of hard decision quantization, we establish a general framework in which motion prediction, quantization, and entropy coding in a hybrid video coding scheme such as H.264 are jointly designed to minimize the actual RD cost on a frame basis. The proposed framework is applicable to optimize any hybrid video coding scheme, provided that specific algorithms are designed corresponding to coding syntaxes of a given standard codec, so as to maintain compatibility with the standard. Corresponding to the baseline profile syntaxes and the main profile syntaxes of H.264, respectively, we have proposed three RD algorithms---a graph-based algorithm for SDQ given motion prediction and quantization step sizes, an algorithm for residual coding optimization given motion prediction, and an iterative overall algorithm for jointly optimizing motion prediction, quantization, and entropy coding---with them embedded in the indicated order. Among the three algorithms, the SDQ design is the core, which is developed based on a given entropy coding method. Specifically, two SDQ algorithms have been developed based on the context adaptive variable length coding (CAVLC) in H.264 baseline profile and the context adaptive binary arithmetic coding (CABAC) in H.264 main profile, respectively. Experimental results for the H.264 baseline codec optimization show that for a set of typical testing sequences, the proposed RD method for H.264 baseline coding achieves a better trade-off between rate and distortion, i.e., 12\% rate reduction on average at the same distortion (ranging from 30dB to 38dB by PSNR) when compared with the RD optimization method implemented in H.264 baseline reference codec. Experimental results for optimizing H.264 main profile coding with CABAC show 10\% rate reduction over a main profile reference codec using CABAC, which also suggests 20\% rate reduction over the RD optimization method implemented in H.264 baseline reference codec, leading to our claim of having developed the best codec in terms of RD performance, while maintaining the compatibility with H.264. By investigating trade-off between distortion and complexity, we have also proposed a designing framework for image/video transcoding with spatial resolution reduction, i.e., to down-sample compressed images/video with an arbitrary ratio in the DCT domain. First, we derive a set of DCT-domain down-sampling methods, which can be represented by a linear transform with double-sided matrix multiplication (LTDS) in the DCT domain. Then, for a pre-selected pixel-domain down-sampling method, we formulate an optimization problem for finding an LTDS to approximate the given pixel-domain method to achieve the best trade-off between visual quality and computational complexity. The problem is then solved by modeling an LTDS with a multi-layer perceptron network and using a structural learning with forgetting algorithm for training the network. Finally, by selecting a pixel-domain reference method with the popular Butterworth lowpass filtering and cubic B-spline interpolation, the proposed framework discovers an LTDS with better visual quality and lower computational complexity when compared with state-of-the-art methods in the literature

Error resilient packet switched H.264 video telephony over third generation networks.

Real-time video communication over wireless networks is a challenging problem because wireless channels suffer from fading, additive noise and interference, which translate into packet loss and delay. Since modern video encoders deliver video packets with decoding dependencies, packet loss and delay can significantly degrade the video quality at the receiver. Many error resilience mechanisms have been proposed to combat packet loss in wireless networks, but only a few were specifically designed for packet switched video telephony over Third Generation (3G) networks. The first part of the thesis presents an error resilience technique for packet switched video telephony that combines application layer Forward Error Correction (FEC) with rateless codes, Reference Picture Selection (RPS) and cross layer optimization. Rateless codes have lower encoding and decoding computational complexity compared to traditional error correcting codes. One can use them on complexity constrained hand-held devices. Also, their redundancy does not need to be fixed in advance and any number of encoded symbols can be generated on the fly. Reference picture selection is used to limit the effect of spatio-temporal error propagation. Limiting the effect of spatio-temporal error propagation results in better video quality. Cross layer optimization is used to minimize the data loss at the application layer when data is lost at the data link layer. Experimental results on a High Speed Packet Access (HSPA) network simulator for H.264 compressed standard video sequences show that the proposed technique achieves significant Peak Signal to Noise Ratio (PSNR) and Percentage Degraded Video Duration (PDVD) improvements over a state of the art error resilience technique known as Interactive Error Control (IEC), which is a combination of Error Tracking and feedback based Reference Picture Selection. The improvement is obtained at a cost of higher end-to-end delay. The proposed technique is improved by making the FEC (Rateless code) redundancy channel adaptive. Automatic Repeat Request (ARQ) is used to adjust the redundancy of the Rateless codes according to the channel conditions. Experimental results show that the channel adaptive scheme achieves significant PSNR and PDVD improvements over the static scheme for a simulated Long Term Evolution (LTE) network. In the third part of the thesis, the performance of the previous two schemes is improved by making the transmitter predict when rateless decoding will fail. In this case, reference picture selection is invoked early and transmission of encoded symbols for that source block is aborted. Simulations for an LTE network show that this results in video quality improvement and bandwidth savings. In the last part of the thesis, the performance of the adaptive technique is improved by exploiting the history of the wireless channel. In a Rayleigh fading wireless channel, the RLC-PDU losses are correlated under certain conditions. This correlation is exploited to adjust the redundancy of the Rateless code and results in higher Rateless code decoding success rate and higher video quality. Simulations for an LTE network show that the improvement was significant when the packet loss rate in the two wireless links was 10%. To facilitate the implementation of the proposed error resilience techniques in practical scenarios, RTP/UDP/IP level packetization schemes are also proposed for each error resilience technique. Compared to existing work, the proposed error resilience techniques provide better video quality. Also, more emphasis is given to implementation issues in 3G networks

Low energy HEVC and VVC video compression hardware

Video compression standards compress a digital video by reducing and removing redundancy in the digital video using computationally complex algorithms. As spatial and temporal resolutions of videos increase, compression efficiencies of video compression algorithms are also increasing. However, increased compression efficiency comes with increased computational complexity. Therefore, it is necessary to reduce computational complexities of video compression algorithms without reducing their visual quality in order to reduce area and energy consumption of their hardware implementations. In this thesis, we propose a novel technique for reducing amount of computations performed by HEVC intra prediction algorithm. We designed low energy, reconfigurable HEVC intra prediction hardware using the proposed technique. We also designed a low energy FPGA implementation of HEVC intra prediction algorithm using the proposed technique and DSP blocks. We propose a reconfigurable VVC intra prediction hardware architecture. We also propose an efficient VVC intra prediction hardware architecture using DSP blocks. We designed low energy VVC fractional interpolation hardware. We propose a novel approximate absolute difference technique. We designed low energy approximate absolute difference hardware using the proposed technique. We propose a novel approximate constant multiplication technique. We designed approximate constant multiplication hardware using the proposed technique. We quantified computation reductions achieved by the proposed techniques and video quality loss caused by the proposed approximation techniques. The proposed approximate absolute difference technique and approximate constant multiplication technique cause very small PSNR loss. The other proposed techniques cause no PSNR loss. We implemented the proposed hardware architectures in Verilog HDL. We mapped the Verilog RTL codes to Xilinx Virtex 6 or Xilinx Virtex 7 FPGAs and estimated their power consumptions using Xilinx XPower Analyzer tool. The proposed techniques significantly reduced power and energy consumptions of these FPGA implementation

A two-stage approach for robust HEVC coding and streaming

The increased compression ratios achieved by the High Efficiency Video Coding (HEVC) standard lead to reduced robustness of coded streams, with increased susceptibility to network errors and consequent video quality degradation. This paper proposes a method based on a two-stage approach to improve the error robustness of HEVC streaming, by reducing temporal error propagation in case of frame loss. The prediction mismatch that occurs at the decoder after frame loss is reduced through the following two stages: (i) at the encoding stage, the reference pictures are dynamically selected based on constraining conditions and Lagrangian optimisation, which distributes the use of reference pictures, by reducing the number of prediction units (PUs) that depend on a single reference; (ii) at the streaming stage, a motion vector (MV) prioritisation algorithm, based on spatial dependencies, selects an optimal sub-set of MVs to be transmitted, redundantly, as side information to reduce mismatched MV predictions at the decoder. The simulation results show that the proposed method significantly reduces the effect of temporal error propagation. Compared to the reference HEVC, the proposed reference picture selection method is able to improve the video quality at low packet loss rates (e.g., 1%) using the same bitrate, achieving quality gains up to 2.3 dB for 10% of packet loss ratio. It is shown, for instance, that the redundant MVs are able to boost the performance achieving quality gains of 3 dB when compared to the reference HEVC, at the cost using 4% increase in total bitrate