An efficient rate control algorithm for a wavelet video codec

Rate control plays an essential role in video coding and transmission to provide the best video quality at the receiver's end given the constraint of certain network conditions. In this paper, a rate control algorithm using the Quality Factor (QF) optimization method is proposed for the wavelet-based video codec and implemented on an open source Dirac video encoder. A mathematical model which we call Rate-QF (R - QF) model is derived to generate the optimum QF for the current coding frame according to the target bitrate. The proposed algorithm is a complete one pass process and does not require complex mathematical calculation. The process of calculating the QF is quite simple and further calculation is not required for each coded frame. The experimental results show that the proposed algorithm can control the bitrate precisely (within 1% of target bitrate in average). Moreover, the variation of bitrate over each Group of Pictures (GOPs) is lower than that of H.264. This is an advantage in preventing the buffer overflow and underflow for real-time multimedia data streaming

Research and developments of Dirac video codec

This thesis was submitted for the degree of Doctor of Philosophy and was awarded by Brunel University.In digital video compression, apart from storage, successful transmission of the compressed video data over the bandwidth limited erroneous channels is another important issue. To enable a video codec for broadcasting application, it is required to implement the corresponding coding tools (e.g. error-resilient coding, rate control etc.). They are normally non-normative parts of a video codec and hence their specifications are not defined in the standard. In Dirac as well, the original codec is optimized for storage purpose only and so, several non-normative part of the encoding tools are still required in order to be able to use in other types of application. Being the "Research and Developments of the Dirac Video Codec" as the research title, phase I of the project is mainly focused on the error-resilient transmission over a noisy channel. The error-resilient coding method used here is a simple and low complex coding scheme which provides the error-resilient transmission of the compressed video bitstream of Dirac video encoder over the packet erasure wired network. The scheme combines source and channel coding approach where error-resilient source coding is achieved by data partitioning in the wavelet transformed domain and channel coding is achieved through the application of either Rate-Compatible Punctured Convolutional (RCPC) Code or Turbo Code (TC) using un-equal error protection between header plus MV and data. The scheme is designed mainly for the packet-erasure channel, i.e. targeted for the Internet broadcasting application. But, for a bandwidth limited channel, it is still required to limit the amount of bits generated from the encoder depending on the available bandwidth in addition to the error-resilient coding. So, in the 2nd phase of the project, a rate control algorithm is presented. The algorithm is based upon the Quality Factor (QF) optimization method where QF of the encoded video is adaptively changing in order to achieve average bitrate which is constant over each Group of Picture (GOP). A relation between the bitrate, R and the QF, which is called Rate-QF (R-QF) model is derived in order to estimate the optimum QF of the current encoding frame for a given target bitrate, R. In some applications like video conferencing, real-time encoding and decoding with minimum delay is crucial, but, the ability to do real-time encoding/decoding is largely determined by the complexity of the encoder/decoder. As we all know that motion estimation process inside the encoder is the most time consuming stage. So, reducing the complexity of the motion estimation stage will certainly give one step closer to the real-time application. So, as a partial contribution toward realtime application, in the final phase of the research, a fast Motion Estimation (ME) strategy is designed and implemented. It is the combination of modified adaptive search plus semi-hierarchical way of motion estimation. The same strategy was implemented in both Dirac and H.264 in order to investigate its performance on different codecs. Together with this fast ME strategy, a method which is called partial cost function calculation in order to further reduce down the computational load of the cost function calculation was presented. The calculation is based upon the pre-defined set of patterns which were chosen in such a way that they have as much maximum coverage as possible over the whole block. In summary, this research work has contributed to the error-resilient transmission of compressed bitstreams of Dirac video encoder over a bandwidth limited error prone channel. In addition to this, the final phase of the research has partially contributed toward the real-time application of the Dirac video codec by implementing a fast motion estimation strategy together with partial cost function calculation idea.BBC R&D and Brunel University

Enabling error-resilient internet broadcasting using motion compensated spatial partitioning and packet FEC for the dirac video codec

Video transmission over the wireless or wired network require protection from channel errors since compressed video bitstreams are very sensitive to transmission errors because of the use of predictive coding and variable length coding. In this paper, a simple, low complexity and patent free error-resilient coding is proposed. It is based upon the idea of using spatial partitioning on the motion compensated residual frame without employing the transform coefficient coding. The proposed scheme is intended for open source Dirac video codec in order to enable the codec to be used for Internet broadcasting. By partitioning the wavelet transform coefficients of the motion compensated residual frame into groups and independently processing each group using arithmetic coding and Forward Error Correction (FEC), robustness to transmission errors over the packet erasure wired network could be achieved. Using the Rate Compatibles Punctured Code (RCPC) and Turbo Code (TC) as the FEC, the proposed technique provides gracefully decreasing perceptual quality over packet loss rates up to 30%. The PSNR performance is much better when compared with the conventional data partitioning only methods. Simulation results show that the use of multiple partitioning of wavelet coefficient in Dirac can achieve up to 8 dB PSNR gain over its existing un-partitioned method

Cooperative systems based signal processing techniques with applications to three-dimensional video transmission

Three-dimensional (3-D) video has recently emerged to offer an immersive multimedia experience that can not be offered by two-dimensional (2-D) video applications. Currently, both industry and academia are focused on delivering 3-D video services to wireless communication systems. Modern video communication systems currently adopt cooperative communication and orthogonal frequency division multiplexing (OFDM) as they are an attractive solution to combat fading in wireless communication systems and achieve high data-rates. However, this strong motivation to transmit the video signals over wireless systems faces many challenges. These are mainly channel bandwidth limitations, variations of signal-to-noise ratio (SNR) in wireless channels, and the impairments in the physical layer such as time varying phase noise (PHN), and carrier frequency offset (CFO). In response to these challenges, this thesis seeks to develop efficient 3-D video transmission methods and signal processing algorithms that can overcome the effects of error-prone wireless channels and impairments in the physical layer. In the first part of the thesis, an efficient unequal error protection (UEP) scheme, called video packet partitioning, and a new 3-D video transceiver structure are proposed. The proposed video transceiver uses switching operations between various UEP schemes based on the packet partitioning to achieve a trade- off between system complexity and performance. Experimental results show that the proposed system achieves significantly high video quality at different SNRs with the lowest possible bandwidth and system complexity compared to direct transmission schemes. The second part of the thesis proposes a new approach to joint source-channel coding (JSCC) that simultaneously assigns source code rates, the number of high and low priority packets, and channel code rates for the application, network, and physical layers, respectively. The proposed JSCC algorithm takes into account the rate budget constraint and the available instantaneous SNR of the best relay selection in cooperative systems. Experimental results show that the proposed JSCC algorithm outperforms existing algorithms in terms of peak signal-to-noise ratio (PSNR). In the third part of the thesis, a computationally efficient training based approach for joint channel, CFO, and PHN estimation in OFDM systems is pro- posed. The proposed estimator is based on an expectation conditional maximization (ECM) algorithm. To compare the estimation accuracy of the proposed estimator, the hybrid Cram´er-Rao lower bound (HCRB) of hybrid parameters of interest is derived. Next, to detect the signal in the presence of PHN, an iterative receiver based on the extended Kalman filter (EKF) for joint data detection and PHN mitigation is proposed. It is demonstrated by numerical simulations that, compared to existing algorithms, the performance of the proposed ECM-based estimator in terms of the mean square error (MSE) is closer to the derived HCRB and outperforms the existing estimation algorithms at moderate-to-high SNRs. Finally, this study extends the research on joint channel, PHN, and CFO estimation one step forward from OFDM systems to cooperative OFDM systems. An iterative algorithm based on the ECM in cooperative OFDM networks in the presence of unknown channel gains, PHNs and CFOs is applied. Moreover, the HCRB for the joint estimation problem in both decode-and-forward (DF) and amplify-and-forward (AF) relay systems is presented. An iterative algorithm based on the EKF for data detection and tracking the unknown time-varying PHN throughout the OFDM data packet is also used. For more efficient 3-D video transmission, the estimation algorithms and UEP schemes based packet portioning were combined to achieve a more robust video bit stream in the presence of PHNs. Applying this combination, simulation results demonstrate that promising bit-error-rate (BER) and PSNR performance can be achieved at the destination at different SNRs and PHN variance. The proposed schemes and algorithms offer solutions for existing problems in the techniques for applications to 3-D video transmission

An efficient rate control algorithm for a wavelet video codec

Rate control plays an essential role in video coding and transmission to provide the best video quality at the receiver's end given the constraint of certain network conditions. In this paper, a rate control algorithm using the Quality Factor (QF) optimization method is proposed for the wavelet-based video codec and implemented on an open source Dirac video encoder. A mathematical model which we call Rate-QF (R - QF) model is derived to generate the optimum QF for the current coding frame according to the target bitrate. The proposed algorithm is a complete one pass process and does not require complex mathematical calculation. The process of calculating the QF is quite simple and further calculation is not required for each coded frame. The experimental results show that the proposed algorithm can control the bitrate precisely (within 1% of target bitrate in average). Moreover, the variation of bitrate over each Group of Pictures (GOPs) is lower than that of H.264. This is an advantage in preventing the buffer overflow and underflow for real-time multimedia data streaming

Error resilience and concealment techniques for high-efficiency video coding

This thesis investigates the problem of robust coding and error concealment in High Efficiency Video Coding (HEVC). After a review of the current state of the art, a simulation study about error robustness, revealed that the HEVC has weak protection against network losses with significant impact on video quality degradation. Based on this evidence, the first contribution of this work is a new method to reduce the temporal dependencies between motion vectors, by improving the decoded video quality without compromising the compression efficiency. The second contribution of this thesis is a two-stage approach for reducing the mismatch of temporal predictions in case of video streams received with errors or lost data. At the encoding stage, the reference pictures are dynamically distributed based on a constrained Lagrangian rate-distortion optimization to reduce the number of predictions from a single reference. At the streaming stage, a prioritization algorithm, based on spatial dependencies, selects a reduced set of motion vectors to be transmitted, as side information, to reduce mismatched motion predictions at the decoder. The problem of error concealment-aware video coding is also investigated to enhance the overall error robustness. A new approach based on scalable coding and optimally error concealment selection is proposed, where the optimal error concealment modes are found by simulating transmission losses, followed by a saliency-weighted optimisation. Moreover, recovery residual information is encoded using a rate-controlled enhancement layer. Both are transmitted to the decoder to be used in case of data loss. Finally, an adaptive error resilience scheme is proposed to dynamically predict the video stream that achieves the highest decoded quality for a particular loss case. A neural network selects among the various video streams, encoded with different levels of compression efficiency and error protection, based on information from the video signal, the coded stream and the transmission network. Overall, the new robust video coding methods investigated in this thesis yield consistent quality gains in comparison with other existing methods and also the ones implemented in the HEVC reference software. Furthermore, the trade-off between coding efficiency and error robustness is also better in the proposed methods

A Novel Rate Control Algorithm for Onboard Predictive Coding of Multispectral and Hyperspectral Images

Predictive coding is attractive for compression onboard of spacecrafts thanks to its low computational complexity, modest memory requirements and the ability to accurately control quality on a pixel-by-pixel basis. Traditionally, predictive compression focused on the lossless and near-lossless modes of operation where the maximum error can be bounded but the rate of the compressed image is variable. Rate control is considered a challenging problem for predictive encoders due to the dependencies between quantization and prediction in the feedback loop, and the lack of a signal representation that packs the signal's energy into few coefficients. In this paper, we show that it is possible to design a rate control scheme intended for onboard implementation. In particular, we propose a general framework to select quantizers in each spatial and spectral region of an image so as to achieve the desired target rate while minimizing distortion. The rate control algorithm allows to achieve lossy, near-lossless compression, and any in-between type of compression, e.g., lossy compression with a near-lossless constraint. While this framework is independent of the specific predictor used, in order to show its performance, in this paper we tailor it to the predictor adopted by the CCSDS-123 lossless compression standard, obtaining an extension that allows to perform lossless, near-lossless and lossy compression in a single package. We show that the rate controller has excellent performance in terms of accuracy in the output rate, rate-distortion characteristics and is extremely competitive with respect to state-of-the-art transform coding

Improved quality block-based low bit rate video coding.

The aim of this research is to develop algorithms for enhancing the subjective quality and coding efficiency of standard block-based video coders. In the past few years, numerous video coding standards based on motion-compensated block-transform structure have been established where block-based motion estimation is used for reducing the correlation between consecutive images and block transform is used for coding the resulting motion-compensated residual images. Due to the use of predictive differential coding and variable length coding techniques, the output data rate exhibits extreme fluctuations. A rate control algorithm is devised for achieving a stable output data rate. This rate control algorithm, which is essentially a bit-rate estimation algorithm, is then employed in a bit-allocation algorithm for improving the visual quality of the coded images, based on some prior knowledge of the images. Block-based hybrid coders achieve high compression ratio mainly due to the employment of a motion estimation and compensation stage in the coding process. The conventional bit-allocation strategy for these coders simply assigns the bits required by the motion vectors and the rest to the residual image. However, at very low bit-rates, this bit-allocation strategy is inadequate as the motion vector bits takes up a considerable portion of the total bit-rate. A rate-constrained selection algorithm is presented where an analysis-by-synthesis approach is used for choosing the best motion vectors in term of resulting bit rate and image quality. This selection algorithm is then implemented for mode selection. A simple algorithm based on the above-mentioned bit-rate estimation algorithm is developed for the latter to reduce the computational complexity. For very low bit-rate applications, it is well-known that block-based coders suffer from blocking artifacts. A coding mode is presented for reducing these annoying artifacts by coding a down-sampled version of the residual image with a smaller quantisation step size. Its applications for adaptive source/channel coding and for coding fast changing sequences are examined