Low-delay Coding Research Articles

Inter-Frame Dependency-Based Rate Control for VVC Low-Delay Coding

In this letter, we propose two solutions for the rate control of the VVC low-delay coding. Both solutions are developed by determining the bit allocation factors for video frames based on their dependency. Specifically, we design the first solution according to the distortion correlation between the key-frame and its subsequent frames. With this solution, the bit allocation factors are determined by applying multi-pass coding on the video to build up the cross-frame distortion model. This model offers us a straightforward way to achieve better rate control performance but results in a rather high complexity. To solve the complexity problem, we propose the second solution based on the difference between frames. In this solution, we construct the bit allocation model and apply it to frames so that we can adaptively determine the allocation factors with a low complexity. The experimental results demonstrate that our proposed two solutions can offer better rate-distortion performances than the state-of-the-art method.

Design of FEC for Low Delay in 5G

In this paper, we consider the design of forward error correction tailored specifically for the low end-to-end latency requirements in 5G networks. We present experimental results that highlight a number of issues with conventional approaches and then introduce a new low delay code construction that achieves a superior throughput-delay tradeoff. We analyze its performance both mathematically and experimentally. The mathematical analysis of throughput and delay requires the development of a number of novel analytic tools based on both queuing and coding theories. We implement the low delay code and evaluate its performance in an experimental test bed.

Burst-Erasure Correcting Codes with Optimal Average Delay

The objective of low-delay codes is to protect communication streams from erasure bursts by minimizing the time between the packet erasure and its reconstruction. Previous work has concentrated on the constant-delay scenario, where all erased packets need to exhibit the same decoding delay. We consider the case of heterogeneous delay, where the objective is to minimize the average delay across the erased packets in a burst. We derive delay lower bounds for the average case, and show that they match the constant-delay bounds only at a single rate point $R=0.5$ . We then construct codes with optimal average delays for the entire range of code rates. The construction for rates $R\leq 0.5$ achieves optimality for every erasure instance, while the construction for rates $R>0.5$ is optimal for a $(1-R)/R$ fraction of all burst instances and close to optimal for the remaining fraction. The paper also studies the benefits of delay heterogeneity within the application of sensor communications. It is shown that a carefully designed code can significantly improve the temporal precision at the receiving node following erasure-burst events.

Source-Interference Recovery Over Broadcast Channels: Asymptotic Bounds and Analog Codes

We consider the problem of joint recovery of a bivariate Gaussian source and of interference over the two-user Gaussian degraded broadcast channel in the presence of common interference. The interference, that is available non-causally at the encoder, is assumed to be Gaussian and correlated to the sources. The tradeoff between the distortion of the sources and the interference estimation error is studied; information-theoretic outer and inner bounds based on ideas from rate-distortion theory and hybrid coding are derived, respectively. More precisely, the outer bound is found by assuming additional knowledge at each user; the inner bound, however, is obtained by analyzing the distortion of a layered hybrid scheme based on proper power splitting, Costa and Wyner–Ziv coding. Low delay and complexity coding schemes based on analog mapping are next proposed. More specifically, parametric mappings based on linear and sawtooth curves are studied and optimized by minimizing an upper bound on the system’s distortion; nonparametric mappings based on joint optimization between the encoder and the decoder using an iterative algorithm are designed. Numerical results show that for the special cases that are previously considered by Abou Saleh et al. (with no fading), the derived outer bound is tighter and the proposed hybrid scheme has a lower complex structure with no loss in performance. In addition, the proposed low delay nonlinear schemes outperform the linear scheme and perform relatively close to the inner bound under certain system settings.

Practical design of delta-sigma multiple description audio coding

Abstract It was recently shown that delta-sigma quantization (DSQ) can be used for optimal multiple description (MD) coding of Gaussian sources. The DSQ scheme combined oversampling, prediction, and noise-shaping in order to trade off side distortion for central distortion in MD coding. It was shown that asymptotically in the dimensions of the resampling, prediction, and noise-shaping filters as well as asymptotically in the quantizer dimensions, all rate-distortion points on the symmetric quadratic Gaussian MD rate-distortion function could be achieved. In this work, we show that this somewhat theoretical framework is suitable for practical low-delay MD audio coding. In particular, we design a practical MD audio coder with two descriptions and provide simulations on real audio data. The simulations demonstrate that even when using low-dimensional noise-shaping, prediction, and resampling filters, it is possible to obtain good quality audio in the presence of packet losses. Simulations on real audio reveal that, contrary to existing designs, it is straightforward to obtain a large number of trade-off points between side distortion and central distortion, which makes the proposed coder suitable for a wide range of applications.

Progressively refined wyner-ziv video coding for visual sensors

Wyner-Ziv video coding constitutes an alluring paradigm for visual sensor networks, offering efficient video compression with low complexity encoding characteristics. This work presents a novel hash-driven Wyner-Ziv video coding architecture for visual sensors, implementing the principles of successively refined Wyner-Ziv coding. To this end, so-called side-information refinement levels are constructed for a number of grouped frequency bands of the discrete cosine transform. The proposed codec creates side-information by means of an original overlapped block motion estimation and pixel-based multihypothesis prediction technique, specifically built around the pursued refinement strategy. The quality of the side-information generated at every refinement level is successively improved, leading to gradually enhanced Wyner-Ziv coding performance. Additionally, this work explores several temporal prediction structures, including a new hierarchical unidirectional prediction structure, providing both temporal scalability and low delay coding. Experimental results include a thorough evaluation of our novel Wyner-Ziv codec, assessing the impact of the proposed successive refinement scheme and the supported temporal prediction structures for a wide range of hash configurations and group of pictures sizes. The results report significant compression gains with respect to benchmark systems in Wyner-Ziv video coding (e.g., up to 42.03% over DISCOVER) as well as versus alternative state-of-the-art schemes refining the side-information.

Efficient Low-Delay Distributed Video Coding

Distributed video coding (DVC) is a video coding paradigm that allows for a low-complexity encoding process by exploiting the temporal redundancies in a video sequence at the decoder side. State-of-the-art DVC systems exhibit a structural coding delay since exploiting the temporal redundancies through motion-compensated interpolation requires the frames to be decoded out of order. To alleviate this problem, we propose a system based on motion-compensated extrapolation that allows for efficient low-delay video coding with low complexity at the encoder. The proposed extrapolation technique first estimates the motion field between the two most recently decoded frames using the Lucas-Kanade algorithm. The obtained motion field is then extrapolated to the current frame using an extrapolation grid. The proposed techniques are implemented into a novel architecture featuring hybrid block-frequency Wyner-Ziv coding as well as mode decision. Results show that having references from both temporal directions in interpolation provides superior rate-distortion performance over a single temporal direction in extrapolation, as expected. However, the proposed extrapolation method is particularly suitable for low-delay coding as it performs better than H.264/AVC intra, and it is even able to outperform the interpolation-based DVC codec from DISCOVER for several sequences.

On Predictive Coding for Erasure Channels Using a Kalman Framework

We present a new design method for robust low-delay coding of auto-regressive (AR) sources for transmission across erasure channels. The method is based on Linear Predictive Coding (LPC) with Kalman estimation at the decoder. The method designs the encoder and decoder offline through an iterative algorithm based on minimization of the trace of the decoder state error covariance. The design method applies to stationary AR sources of any order. Simulation results show considerable performance gains, when the transmitted quantized prediction errors are subject to loss, in terms of Signal-to-Noise Ratio (SNR) compared to the same coding framework optimized for no loss. We furthermore investigate the impact on decoding performance when channel losses are correlated. We find that the method still provides substantial improvements in this case despite being designed for i.i.d. losses.

Distributed Predictive Coding for Spatio-Temporally Correlated Sources

Distributed coding of correlated sources with memory poses a number of considerable challenges that threaten its practical application, particularly (but not only) in the context of sensor networks. This problem is strongly motivated by the obvious observation that most common sources exhibit temporal correlations that may be at least as important as spatial or intersource correlations. This paper presents an analysis of the underlying tradeoffs, paradigms for coding systems, and approaches for distributed predictive coder design optimization. Motivated by practical limitations on both complexity and delay (especially for dense sensor networks) the focus here is on predictive coding. From the source coding perspective, the most basic tradeoff (and difficulty) is due to conflicts that arise between distributed coding and prediction, wherein ldquostandardrdquo distributed quantization of the prediction errors, if coupled with imposition of zero decoder drift, would drastically compromise the predictor performance and hence the ability to exploit temporal correlations. Another challenge arises from instabilities in the design of closed-loop predictors, whose impact has been observed in the past, but is greatly exacerbated in the case of distributed coding. In the distributed predictive coder design, we highlight the fundamental tradeoffs encountered within a more general paradigm where decoder drift is allowable or unavoidable, and must be effectively accounted for and controlled. We derive an overall design optimization method for distributed predictive coding that avoids the pitfalls of naive distributed predictive quantization and produces an optimized low complexity and low delay coding system. The proposed iterative algorithms for distributed predictive coding subsume traditional single-source predictive coding and memoryless distributed coding as extreme special cases.

Joint Rate Control Algorithm for Low-Delay MPEG-4 Object-Based Video Encoding

This paper proposes an improved rate control algorithm for jointly encoding multiple arbitrarily shaped video objects in the context of low-delay MPEG-4 compliant video coding. The algorithm provides adequate mechanisms for dealing with deviations between the ideal and the actual behavior of video scene encoders, notably: 1) compensation mechanisms (e.g., rate control decisions) that are able to track these deviations and compensate them to allow a stable and efficient operation of the encoder, and 2) adaptation mechanisms (e.g., estimation of model parameters) that are able to instantaneously represent the actual behavior of the encoder and its rate controller. The proposed solution efficiently allocates the available resources, i.e., target bit rate and bitstream buffer space, aiming at maximizing the average scene quality and minimizing quality fluctuations along time and among the various video objects. The results show that this solution outperforms the usual reference solutions, notably those specified in the rate control informative annex of the MPEG-4 visual standard.

Spatial-Aided Low-Delay Wyner-Ziv Video Coding

In distributed video coding, the side information (SI) quality plays an important role in Wyner-Ziv (WZ) frame coding. Usually, SI is generated at the decoder by the motion-compensated interpolation (MCI) from the past and future key frames under the assumption that the motion trajectory between the adjacent frames is translational with constant velocity. However, this assumption is not always true and thus, the coding efficiency for WZ coding is often unsatisfactory in video with high and/or irregular motion. This situation becomes more serious in low-delay applications since only motion-compensated extrapolation (MCE) can be applied to yield SI. In this paper, a spatial-aided Wyner-Ziv video coding (WZVC) in low-delay application is proposed. In SA-WZVC, at the encoder, each WZ frame is coded as performed in the existing common Wyner-Ziv video coding scheme and meanwhile, the auxiliary information is also coded with the low-complexity DPCM. At the decoder, for the WZ frame decoding, auxiliary information should be decoded firstly and then SI is generated with the help of this auxiliary information by the spatial-aided motion-compensated extrapolation (SA-MCE). Theoretical analysis proved that when a good tradeoff between the auxiliary information coding and WZ frame coding is achieved, SA-WZVC is able to achieve better rate distortion performance than the conventional MCE-based WZVC without auxiliary information. Experimental results also demonstrate that SAWZVC can efficiently improve the coding performance of WZVC in low-delay application.

The Use of MPEG-4 AVC in the Contribution Market

This paper describes performance evaluation of MPEG-4 AVC and JPEG 2000 compression technologies for high-definition video signals at a wide range of high bit rates. Brief technical overviews of both standards are first presented, and then simulations are performed on an extensive set of HD video sequences are discussed. Two MPEG-4 AVC modes: an all-intra coding mode and a low-delay inter-predictive coding mode are used. Based on the simulation results, it is observed that at high bit rates, the performance of both modes of MPEG-4 AVC is quite similar to that of JPEG 2000. However, at medium and low ranges of bit rates, MPEG-4 AVC generally outperforms JPEG 2000 with a greater visual difference when the inter-predictive mode is employed.

REAL-TIME SPEECH COMPRESSION BY USING CODE EXCITED LINEAR PREDICTION ALGORITHM

A lot of effort has been spent over the last few years in the development of digital speech coding methods and their subsequent standardization. Algorithms have evolved which provide good quality speech at sub 8 kbps bit rates although at a much computational expense. Speech compression is proposed based on code excited linear prediction algorithm and implementation in DSP algorithm. Algorithm based on three-stage technique which involves simulate, evaluate, debug and implementation in G.723 low delay code excited linear prediction (LD-CELP)[4] algorithm. First stage, the algorithm is evaluated via simulation to determine whether it meets the design criterion. Then, it is implemented in real-time based an object oriented approach. After the algorithm is thoroughly tested, it is further refined to obtain tighter and faster coding. This technique can be applied to other real-time DSP algorithms. A simulation result shows that better speech quality is obtained. The techniques described in this paper are applicable to any other speech codec.

Improved rate control via dynamic frame-rate controlling and Kalman filtering for low-delay video coding

This study proposes a rapid rate-control framework for low-delay video coding. The proposed framework includes a fast frame-rate controller, a frame-level bit-allocation operator, and an adaptive rate-quantization (R-Q) model. The frame-rate controller and the frame-level bit-allocation operator determine the encoding frame rate per time slot and the bit target per frame, which specify motion continuity and consistency of quality, respectively. When a cluster of macroblocks (MBs) in an encoding frame is set by a progressive union process, the adaptive R-Q model is modified by the Kalman filter. The newest R-Q characteristic linear curves of the adaptive R-Q model can be used to obtain the MB-level quantization parameters in a new cluster of MBs (COB). The proposed new framework exhibits higher objective and perceptual qualities than the TMN8 rate control, using a TMN11 frame-rate control module, with a lower computational load.

Decreasing distortion using low delay codes for bursty packet loss channels

The strict delay constraints of real-time communication applications in packet networks limit the use of automatic repeat request (ARQ) (retransmission systems) and error correction codes with extensive interleaving and decoding over long intervals. Since packet losses can introduce significant impairments, we study the effectiveness of low delay channel coding techniques to increase transmission quality across links with bursty losses. Specifically, we consider the benefits of the newly discovered class of low delay convolutional codes known as maximally short codes. By analyzing a Gaussian source transmitted over a Gilbert-Elliott channel, we demonstrate that these codes can achieve significant gains in comparison to uncoded transmission schemes or traditional coded schemes employing Reed-Solomon block codes. To complement and validate the theoretical analysis we also present results from informal listening tests with a voice-over-IP application.

Wavelet packet filterbanks for low time delay audio coding

We study the application of wavelet packet filterbanks to low bit-rate transparent audio coding, taking the audio coders' delay requirements into account, and propose low-delay coders based on wavelet packet filterbanks. We first develop a method of comparison between filterbanks for perceptual audio coding by estimating the necessary bit-rate for a transparent compression. We use this comparison method in order to select the best filters for our audio compression scheme, from a large set of orthogonal and biorthogonal wavelets. Different wavelet filters may be used at different stages of the tree-structured decomposition with a constraint on the overall delay taken into account. The optimization is carried out with a simulated annealing procedure, proposing two wavelet packet filterbanks, exhibiting average and low delays. They are inserted in a complete audio coder that employs vector quantization and considers psychoacoustic models. The use of the proposed filterbanks leads to the design of a new bit allocation procedure, taking into account the lack of selectivity of the equivalent synthesis filters in a wavelet packet filterbank. The resulting audio scheme is validated through listening tests. The wavelet packet filterbanks are shown to be a promising tool for audio coding, especially for low-delay coding: with average delay, the quality of the wavelet packet filterbanks is as good as with MPEG-1 Layer-2, both with 80 kb/s, and when reducing the delay to 200 samples, 96 kb/s are needed to achieve the same quality.

Shape representation and coding of visual objets in multimedia applications — An overview

Emerging multimedia applications have created the need for new functionalities in digital communications. Whereas existing compression standards only deal with the audio-visual scene at a frame level, it is now necessary to handle individual objects separately, thus allowing scalable transmission as well as interactive scene recomposition by the receiver. The future MPEG-4 standard aims at providing compression tools addressing these functionalities. Unlike existing frame-based standards, the corresponding coding schemes need to encode shape information explicitly. This paper reviews existing solutions to the problem of shape representation and coding. Region and contour coding techniques are presented and their performance is discussed, considering coding efficiency and rate-distortion control capability, as well as flexibility to application requirements such as progressive transmission, low-delay coding, and error robustness.

IMAGE: a low cost, low power video processor for high quality motion estimation in MPEG-2 encoding

A low cost low power architecture dedicated to perform high quality motion estimation on MPEG-2 CCIR 601 sequences is presented. The chip implements a new high performance motion estimation algorithm based on a modified genetic search strategy that can be enhanced by tracking motion vectors through successive frames. When tested on several sequences at different bit rates, the algorithm delivers nearly full search quality (less than -0.1 dB for a /spl plusmn/75 H/V search range) while decreasing the processing power to 0.5%. The proposed MIMD processor exposes software programmability at different levels allowing the user to define his own searching strategy and combine multiple chips in Master-Salve configuration to meet the required processing power. Moreover post-processing of motion vectors, computation of dual prime vectors for low delay coding and selection of macroblock prediction mode can be programmed on this architecture. A low power strategy was also developed that mainly relies on an adaptive clocking scheme and low power caches implementation. The chip has been integrated in a 0.35 /spl mu/m 5L CMOS technology on an area of 50 mm/sup 2/.

Voice coding communication system and apparatus therefor

A low-delay code excited linear prediction (LD-CELP) voice coding systemapplied to a scheme, in which the transmitting side interrupts transmission during the voice-nonactive period and the receiving side generates and outputs a comfort noise during the voice-nonactive period. At the transmitting side, when voice non activity is detected by the voice activity detector, the CN flag indicating the interruption of transmission is sent from the CN flag generator and shortly thereafter a background noise from the LD-CELP encoder is sent, followed by the interruption of transmission. At the receiving side, when the background noise following the CN flag is decoded by the LD-CELP decoder, the internal gain and synthesis filter coefficients are held, which is subsequently used to decode the input from the pseudo-noise generator.

Code-excited linear predictive coding with low delay for speech or audio signals

A code-excited linear-predictive (CELP) coder for speech or audio transmission at compressed (e.g., 16 kb/s) data rates is adapted for low-delay (e.g., less than five ms. per vector) coding by performing spectral analysis of at least a portion of a previous frame of simulated decoded speech to determine a synthesis filter of a much higher order than conventionally used for decoding synthesis and then transmitting only the index for the vector which produces the lowest internal error signal. Modified perceptual weighting parameters and a novel use of postfiltering greatly improve tandeming of a number of encodings and decodings while retaining high quality reproduction.