On the Effectiveness of Video Recolouring as an Uplink-model Video Coding Technique

For decades, conventional video compression formats have advanced via incremental improvements with each subsequent standard achieving better rate-distortion (RD) efficiency at the cost of increased encoder complexity compared to its predecessors. Design efforts have been driven by common multi-media use cases such as video-on-demand, teleconferencing, and video streaming, where the most important requirements are low bandwidth and low video playback latency. Meeting these requirements involves the use of computa- tionally expensive block-matching algorithms which produce excellent compression rates and quick decoding times. However, emerging use cases such as Wireless Video Sensor Networks, remote surveillance, and mobile video present new technical challenges in video compression. In these scenarios, the video capture and encoding devices are often power-constrained and have limited computational resources available, while the decoder devices have abundant resources and access to a dedicated power source. To address these use cases, codecs must be power-aware and offer a reasonable trade-off between video quality, bitrate, and encoder complexity. Balancing these constraints requires a complete rethinking of video compression technology. The uplink video-coding model represents a new paradigm to address these low-power use cases, providing the ability to redistribute computational complexity by offloading the motion estimation and compensation steps from encoder to decoder. Distributed Video Coding (DVC) follows this uplink model of video codec design, and maintains high quality video reconstruction through innovative channel coding techniques. The field of DVC is still early in its development, with many open problems waiting to be solved, and no defined video compression or distribution standards. Due to the experimental nature of the field, most DVC codec to date have focused on encoding and decoding the Luma plane only, which produce grayscale reconstructed videos. In this thesis, a technique called “video recolouring” is examined as an alternative to DVC. Video recolour- ing exploits the temporal redundancies between colour planes, reducing video bitrate by removing Chroma information from specific frames and then recolouring them at the decoder. A novel video recolouring algorithm called Motion-Compensated Recolouring (MCR) is proposed, which uses block motion estimation and bi-directional weighted motion-compensation to reconstruct Chroma planes at the decoder. MCR is used to enhance a conventional base-layer codec, and shown to reduce bitrate by up to 16% with only a slight decrease in objective quality. MCR also outperforms other video recolouring algorithms in terms of objective video quality, demonstrating up to 2 dB PSNR improvement in some cases

Improved Side Information Generation for Distributed Video Coding by Exploiting Spatial and Temporal Correlations

Distributed Video Coding (DVC) is a new paradigm in video coding, which is receiving a lot of interests nowadays. Side Information (SI) generation is a key function in the DVC decoder, and plays a key-role in determining the performance of the codec. This paper proposes an improved motion compensated frame interpolation for SI generation in DVC, which exploits both spatial and temporal correlations in the sequences. Partially decoded Wyner-Ziv (WZ) frames, based on initial SI by motion compensated temporal interpolation, are exploited to improve the performance of the whole SI generation. More specifically, an enhanced temporal frame interpolation is proposed, including motion vector refinement and smoothing, optimal compensation mode selection, and a new matching criterion for motion estimation. The improved SI technique is also applied to a new hybrid spatial and temporal error concealment scheme to conceal errors in WZ frames, where the error-concealed results from spatial concealment are used to improve the performance of temporal concealment. Simulation results show that the proposed scheme can achieve up to 1.0 dB improvement in rate distortion performance in WZ frames for video with high motion, when compared to state-of-the-art DVC. In addition, both the objective and perceptual quality of the corrupted sequences are significantly improved by the proposed hybrid error concealment scheme, outperforming both spatial and temporal concealments alone

Intelligent Side Information Generation in Distributed Video Coding

Distributed video coding (DVC) reverses the traditional coding paradigm of complex encoders allied with basic decoding to one where the computational cost is largely incurred by the decoder. This is attractive as the proven theoretical work of Wyner-Ziv (WZ) and Slepian-Wolf (SW) shows that the performance by such a system should be exactly the same as a conventional coder. Despite the solid theoretical foundations, current DVC qualitative and quantitative performance falls short of existing conventional coders and there remain crucial limitations. A key constraint governing DVC performance is the quality of side information (SI), a coarse representation of original video frames which are not available at the decoder. Techniques to generate SI have usually been based on linear motion compensated temporal interpolation (LMCTI), though these do not always produce satisfactory SI quality, especially in sequences exhibiting non-linear motion. This thesis presents an intelligent higher order piecewise trajectory temporal interpolation (HOPTTI) framework for SI generation with original contributions that afford better SI quality in comparison to existing LMCTI-based approaches. The major elements in this framework are: (i) a cubic trajectory interpolation algorithm model that significantly improves the accuracy of motion vector estimations; (ii) an adaptive overlapped block motion compensation (AOBMC) model which reduces both blocking and overlapping artefacts in the SI emanating from the block matching algorithm; (iii) the development of an empirical mode switching algorithm; and (iv) an intelligent switching mechanism to construct SI by automatically selecting the best macroblock from the intermediate SI generated by HOPTTI and AOBMC algorithms. Rigorous analysis and evaluation confirms that significant quantitative and perceptual improvements in SI quality are achieved with the new framework

Side information exploitation, quality control and low complexity implementation for distributed video coding

Distributed video coding (DVC) is a new video coding methodology that shifts the highly complex motion search components from the encoder to the decoder, such a video coder would have a great advantage in encoding speed and it is still able to achieve similar rate-distortion performance as the conventional coding solutions. Applications include wireless video sensor networks, mobile video cameras and wireless video surveillance, etc. Although many progresses have been made in DVC over the past ten years, there is still a gap in RD performance between conventional video coding solutions and DVC. The latest development of DVC is still far from standardization and practical use. The key problems remain in the areas such as accurate and efficient side information generation and refinement, quality control between Wyner-Ziv frames and key frames, correlation noise modelling and decoder complexity, etc. Under this context, this thesis proposes solutions to improve the state-of-the-art side information refinement schemes, enable consistent quality control over decoded frames during coding process and implement highly efficient DVC codec. This thesis investigates the impact of reference frames on side information generation and reveals that reference frames have the potential to be better side information than the extensively used interpolated frames. Based on this investigation, we also propose a motion range prediction (MRP) method to exploit reference frames and precisely guide the statistical motion learning process. Extensive simulation results show that choosing reference frames as SI performs competitively, and sometimes even better than interpolated frames. Furthermore, the proposed MRP method is shown to significantly reduce the decoding complexity without degrading any RD performance. To minimize the block artifacts and achieve consistent improvement in both subjective and objective quality of side information, we propose a novel side information synthesis framework working on pixel granularity. We synthesize the SI at pixel level to minimize the block artifacts and adaptively change the correlation noise model according to the new SI. Furthermore, we have fully implemented a state-of-the-art DVC decoder with the proposed framework using serial and parallel processing technologies to identify bottlenecks and areas to further reduce the decoding complexity, which is another major challenge for future practical DVC system deployments. The performance is evaluated based on the latest transform domain DVC codec and compared with different standard codecs. Extensive experimental results show substantial and consistent rate-distortion gains over standard video codecs and significant speedup over serial implementation. In order to bring the state-of-the-art DVC one step closer to practical use, we address the problem of distortion variation introduced by typical rate control algorithms, especially in a variable bit rate environment. Simulation results show that the proposed quality control algorithm is capable to meet user defined target distortion and maintain a rather small variation for sequence with slow motion and performs similar to fixed quantization for fast motion sequence at the cost of some RD performance. Finally, we propose the first implementation of a distributed video encoder on a Texas Instruments TMS320DM6437 digital signal processor. The WZ encoder is efficiently implemented, using rate adaptive low-density-parity-check accumulative (LDPCA) codes, exploiting the hardware features and optimization techniques to improve the overall performance. Implementation results show that the WZ encoder is able to encode at 134M instruction cycles per QCIF frame on a TMS320DM6437 DSP running at 700MHz. This results in encoder speed 29 times faster than non-optimized encoder implementation. We also implemented a highly efficient DVC decoder using both serial and parallel technology based on a PC-HPC (high performance cluster) architecture, where the encoder is running in a general purpose PC and the decoder is running in a multicore HPC. The experimental results show that the parallelized decoder can achieve about 10 times speedup under various bit-rates and GOP sizes compared to the serial implementation and significant RD gains with regards to the state-of-the-art DISCOVER codec

REGION-BASED ADAPTIVE DISTRIBUTED VIDEO CODING CODEC

The recently developed Distributed Video Coding (DVC) is typically suitable for the applications where the conventional video coding is not feasible because of its inherent high-complexity encoding. Examples include video surveillance usmg wireless/wired video sensor network and applications using mobile cameras etc. With DVC, the complexity is shifted from the encoder to the decoder. The practical application of DVC is referred to as Wyner-Ziv video coding (WZ) where an estimate of the original frame called "side information" is generated using motion compensation at the decoder. The compression is achieved by sending only that extra information that is needed to correct this estimation. An error-correcting code is used with the assumption that the estimate is a noisy version of the original frame and the rate needed is certain amount of the parity bits. The side information is assumed to have become available at the decoder through a virtual channel. Due to the limitation of compensation method, the predicted frame, or the side information, is expected to have varying degrees of success. These limitations stem from locationspecific non-stationary estimation noise. In order to avoid these, the conventional video coders, like MPEG, make use of frame partitioning to allocate optimum coder for each partition and hence achieve better rate-distortion performance. The same, however, has not been used in DVC as it increases the encoder complexity. This work proposes partitioning the considered frame into many coding units (region) where each unit is encoded differently. This partitioning is, however, done at the decoder while generating the side-information and the region map is sent over to encoder at very little rate penalty. The partitioning allows allocation of appropriate DVC coding parameters (virtual channel, rate, and quantizer) to each region. The resulting regions map is compressed by employing quadtree algorithm and communicated to the encoder via the feedback channel. The rate control in DVC is performed by channel coding techniques (turbo codes, LDPC, etc.). The performance of the channel code depends heavily on the accuracy of virtual channel model that models estimation error for each region. In this work, a turbo code has been used and an adaptive WZ DVC is designed both in transform domain and in pixel domain. The transform domain WZ video coding (TDWZ) has distinct superior performance as compared to the normal Pixel Domain Wyner-Ziv (PDWZ), since it exploits the ' spatial redundancy during the encoding. The performance evaluations show that the proposed system is superior to the existing distributed video coding solutions. Although the, proposed system requires extra bits representing the "regions map" to be transmitted, fuut still the rate gain is noticeable and it outperforms the state-of-the-art frame based DVC by 0.6-1.9 dB. The feedback channel (FC) has the role to adapt the bit rate to the changing ' statistics between the side infonmation and the frame to be encoded. In the unidirectional scenario, the encoder must perform the rate control. To correctly estimate the rate, the encoder must calculate typical side information. However, the rate cannot be exactly calculated at the encoder, instead it can only be estimated. This work also prbposes a feedback-free region-based adaptive DVC solution in pixel domain based on machine learning approach to estimate the side information. Although the performance evaluations show rate-penalty but it is acceptable considering the simplicity of the proposed algorithm. vii