On the Effects of Sender-Receiver Concealment Mismatch on Multimedia Communication Optimization

A large number of performance optimization algorithms for multimedia communications, including rate-distortion optimized schemes, rely on knowing the decoder behavior in case of data loss, i.e., the decoder-side error concealment technique. However, for the specific case of video coding, standards do not specify it, thus different decoders may - and typically do - use different concealment techniques. This work investigates the impact of assuming, in the transmission optimization phase, a concealment algorithm different from the one that is actually used by the decoder, in order to determine which are the best assumptions to use at the transmitter. Firstly, we investigate the typical performance provided by ten concealment techniques belonging to three widely used algorithmic families (spatial, temporal and mixed). Then, we assess the impact that an incorrect concealment assumption causes, in terms of both packet transmission policy changes and video quality degradation, using a simple rate-distortion transmission optimization technique that targets a generic two QoS-level network. Simulation results over several standard video sequences show that the performance impact of incorrectly assuming the decoder-side concealment technique may be significant but it is limited if the two techniques belong to the same algorithmic family. Moreover, the impact on performance caused by incorrect assumptions is strongly mitigated if the decoder employs a high-performance concealment algorithm. Finally, the impact on the performance of several parameters such as the encoding pattern, the packet loss statistics (uniform and burst losses) and the amount of high-priority traffic is evaluated, showing that the conclusions can be confidently applied to actual multimedia communication scenarios

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

Error concealment-aware encoding for robust video transmission

In this paper an error concealment-aware encoding scheme is proposed to improve the quality of decoded video in broadcast environments prone to transmission errors and data loss. The proposed scheme is based on a scalable coding approach where the best error concealment (EC) methods to be used at the decoder are optimally determined at the encoder and signalled to the decoder through SEI messages. Such optimal EC modes are found by simulating transmission losses followed by a lagrangian optimisation of the signalling rate - EC distortion cost. A generalised saliency-weighted distortion is used and the residue between coded frames and their EC substitutes is encoded using a rate-controlled enhancement layer. When data loss occurs the decoder uses the signalling information is used at the decoder, in case of data loss, to improve the reconstruction quality. The simulation results show that the proposed method achieves consistent quality gains in comparison with other reference methods and previous works. Using only the EC mode signalling, i.e., without any residue transmitted in the enhancement layer, an average PSNR gain up to 2.95 dB is achieved, while using the full EC-aware scheme, i.e., including residue encoded in the enhancement layer, the proposed scheme outperforms other comparable methods, with PSNR gain up to 3.79 dB

Error-resilient multi-view video plus depth based 3-D video coding

Three Dimensional (3-D) video, by definition, is a collection of signals that can provide depth perception of a 3-D scene. With the development of 3-D display technologies and interactive multimedia systems, 3-D video has attracted significant interest from both industries and academia with a variety of applications. In order to provide desired services in various 3-D video applications, the multiview video plus depth (MVD) representation, which can facilitate the generation of virtual views, has been determined to be the best format for 3-D video data. Similar to 2-D video, compressed 3-D video is highly sensitive to transmission errors due to errors propagated from the current frame to the future predicted frames. Moreover, since the virtual views required for auto-stereoscopic displays are rendered from the compressed texture videos and depth maps, transmission errors of the distorted texture videos and depth maps can be further propagated to the virtual views. Besides, the distortions in texture and depth show different effects on the rendering views. Therefore, compared to the reliability of the transmission of the 2-D video, error-resilient texture video and depth map coding are facing major new challenges. This research concentrates on improving the error resilience performance of MVD-based 3-D video in packet loss scenarios. Based on the analysis of the propagating behaviour of transmission errors, a Wyner-Ziv (WZ)-based error-resilient algorithm is first designed for coding of the multi-view video data or depth data. In this scheme, an auxiliary redundant stream encoded according to WZ principle is employed to protect a primary stream encoded with standard multi-view video coding codec. Then, considering the fact that different combinations of texture and depth coding mode will exhibit varying robustness to transmission errors, a rate-distortion optimized mode switching scheme is proposed to strike the optimal trade-off between robustness and compression effciency. In this approach, the texture and depth modes are jointly optimized by minimizing the overall distortion of both the coded and synthesized views subject to a given bit rate. Finally, this study extends the research on the reliable transmission of view synthesis prediction (VSP)-based 3-D video. In order to mitigate the prediction position error caused by packet losses in the depth map, a novel disparity vector correction algorithm is developed, where the corrected disparity vector is calculated from the depth error. To facilitate decoder error concealment, the depth error is recursively estimated at the decoder. The contributions of this dissertation are multifold. First, the proposed WZbased error-resilient algorithm can accurately characterize the effect of transmission error on multi-view distortion at the transform domain in consideration of both temporal and inter-view error propagation, and based on the estimated distortion, this algorithm can perform optimal WZ bit allocation at the encoder through explicitly developing a sophisticated rate allocation strategy. This proposed algorithm is able to provide a finer granularity in performing rate adaptivity and unequal error protection for multi-view data, not only at the frame level, but also at the bit-plane level. Secondly, in the proposed mode switching scheme, a new analytic model is formulated to optimally estimate the view synthesis distortion due to packet losses, in which the compound impact of the transmission distortions of both the texture video and the depth map on the quality of the synthesized view is mathematically analysed. The accuracy of this view synthesis distortion model is demonstrated via simulation results and, further, the estimated distortion is integrated into a rate-distortion framework for optimal mode switching to achieve substantial performance gains over state-of-the-art algorithms. Last, but not least, this dissertation provides a preliminary investigation of VSP-based 3-D video over unreliable channel. In the proposed disparity vector correction algorithm, the pixel-level depth map error can be precisely estimated at the decoder without the deterministic knowledge of the error-free reconstructed depth. The approximation of the innovation term involved in depth error estimation is proved theoretically. This algorithm is very useful to conceal the position-erroneous pixels whose disparity vectors are correctly received

Signal Coding Approaches for Spatial Audio and Unreliable Networks

This dissertation is divided into two parts. The first part is concerned with developing algorithms for the compression of emerging 3D audio format, while the second part investigates optimization techniques for error-resilient predictive compression systems design.In the first part, advances in development of compression algorithms for higher order ambisonics (HOA) data is presented. HOA has proven to be the method of choice in virtual reality applications, given its capability in reproducing spatial audio and its rendering flexibility. Recent standardization for HOA compression adopted a framework wherein HOA data are decomposed into principal components that are then encoded by standard audio coding, i.e., frequency domain quantization and entropy coding to exploit psychoacoustic redundancy. A noted shortcoming of this approach is the occasional mismatch in principal components across blocks, and the resulting suboptimal transitions in the data fed to the audio coder. In this dissertation, we propose a framework where singular value decomposition (SVD) is performed after transformation to the frequency domain via the modified discrete cosine transform (MDCT). This framework not only ensures smooth transition across blocks, but also enables frequency dependent SVD for better energy compaction. Moreover, we introduce a novel noise substitution technique to compensate for suppressed ambient energy in discarded higher order ambisonics channels, which significantly enhances the perceptual quality of the reconstructed HOA signal. In the next step, to reduce the burden of side information, a new encoding architecture is presented, where transform matrices are estimated backward-adaptively. This framework allows a more frequent usage of optimal SVD, thereby approaching the full potential of frequencydomain SVD. Also the division of HOA data into predominant and ambient components in current schemes, is difficult to perceptually optimize and ignores spatial inter channel masking effects. To address this issues, a new encoding framework for compression of HOA data is presented, where a null-space basis vector extension technique enables all compression to be performed in the SVD domain, and a jointly computed common masking threshold accounts for effects of spatial masking across components.The second part is concerned with developing optimization techniques for error-resilient predictive compression systems design. Prediction is used in virtually all compression systems and when such a compressed signal is transmitted over unreliable networks, packet losses can lead to significant error propagation through the prediction loop. Despite this, the conventional design technique completely ignores the effect of packet losses, and estimates the prediction parameters to minimize the mean squared prediction error, and optimizes the quantizer to minimize the reconstruction error at the encoder. While some design techniques have been proposed toaccurately estimate and minimize the end-to-end distortion (EED) at the decoderthat accounts for packet losses, they operate in a closed-loop, which introduces a mismatch between statistics used for design and statistics used in operation, causing a negative impact on convergenceand stability of the design procedure. The first contribution of the dissertation is this part is proposing an effective technique for designing a compression system with a first order linear predictor, that accounts for the instability caused by error propagation due to packet losses, and enjoys stable statistics during design by employing open-loop iterations that on convergence mimic closed loop operation.End-to-end distortion (EED) estimation, accounting for error propagationand concealment at the decoder, has been originally developed for video coding, and enables optimal rate-distortion (RD) decisions at the encoder. However, this approach was limited to the video coder’ssimple setting of a single tap constant coefficient temporal predictor. This thesis considerably generalized the framework to account for: i) high order prediction filters, and ii) filter adaptation to localsignal statistics. We demonstrate how this EED estimatecan be leveraged, by an encoder with short and long term linearprediction, to improve RD decisions and achieve major performance gains. The approach is further extended to estimate EED in speech coders. The error propagation problem is exacerbated in this case, as standard coders not only predict the signal from past frames, but also the parameters (in the line spectral frequency domain) employed for such prediction. Hence, the prediction loop propagates errors in the reconstructed signal as well as errors in the prediction parameters. A recursive algorithm is proposed to estimate, at the encoder, the overall EED, by the subterfuge of parallel tracking of decoder statistics for prediction parameters and signal reconstructions, in their respective domains, which are then combined to obtain the ultimate EED estimate

Multimedia over wireless ip networks:distortion estimation and applications.

2006/2007This thesis deals with multimedia communication over unreliable and resource constrained IP-based packet-switched networks. The focus is on estimating, evaluating and enhancing the quality of streaming media services with particular regard to video services. The original contributions of this study involve mainly the development of three video distortion estimation techniques and the successive definition of some application scenarios used to demonstrate the benefits obtained applying such algorithms. The material presented in this dissertation is the result of the studies performed within the Telecommunication Group of the Department of Electronic Engineering at the University of Trieste during the course of Doctorate in Information Engineering. In recent years multimedia communication over wired and wireless packet based networks is exploding. Applications such as BitTorrent, music file sharing, multimedia podcasting are the main source of all traffic on the Internet. Internet radio for example is now evolving into peer to peer television such as CoolStreaming. Moreover, web sites such as YouTube have made publishing videos on demand available to anyone owning a home video camera. Another challenge in the multimedia evolution is inside the house where videos are distributed over local WiFi networks to many end devices around the house. More in general we are assisting an all media over IP revolution, with radio, television, telephony and stored media all being delivered over IP wired and wireless networks. All the presented applications require an extreme high bandwidth and often a low delay especially for interactive applications. Unfortunately the Internet and the wireless networks provide only limited support for multimedia applications. Variations in network conditions can have considerable consequences for real-time multimedia applications and can lead to unsatisfactory user experience. In fact, multimedia applications are usually delay sensitive, bandwidth intense and loss tolerant applications. In order to overcame this limitations, efficient adaptation mechanism must be derived to bridge the application requirements with the transport medium characteristics. Several approaches have been proposed for the robust transmission of multimedia packets; they range from source coding solutions to the addition of redundancy with forward error correction and retransmissions. Additionally, other techniques are based on developing efficient QoS architectures at the network layer or at the data link layer where routers or specialized devices apply different forwarding behaviors to packets depending on the value of some field in the packet header. Using such network architecture, video packets are assigned to classes, in order to obtain a different treatment by the network; in particular, packets assigned to the most privileged class will be lost with a very small probability, while packets belonging to the lowest priority class will experience the traditional best–effort service. But the key problem in this solution is how to assign optimally video packets to the network classes. One way to perform the assignment is to proceed on a packet-by-packet basis, to exploit the highly non-uniform distortion impact of compressed video. Working on the distortion impact of each individual video packet has been shown in recent years to deliver better performance than relying on the average error sensitivity of each bitstream element. The distortion impact of a video packet can be expressed as the distortion that would be introduced at the receiver by its loss, taking into account the effects of both error concealment and error propagation due to temporal prediction. The estimation algorithms proposed in this dissertation are able to reproduce accurately the distortion envelope deriving from multiple losses on the network and the computational complexity required is negligible in respect to those proposed in literature. Several tests are run to validate the distortion estimation algorithms and to measure the influence of the main encoder-decoder settings. Different application scenarios are described and compared to demonstrate the benefits obtained using the developed algorithms. The packet distortion impact is inserted in each video packet and transmitted over the network where specialized agents manage the video packets using the distortion information. In particular, the internal structure of the agents is modified to allow video packets prioritization using primarily the distortion impact estimated by the transmitter. The results obtained will show that, in each scenario, a significant improvement may be obtained with respect to traditional transmission policies. The thesis is organized in two parts. The first provides the background material and represents the basics of the following arguments, while the other is dedicated to the original results obtained during the research activity. Referring to the first part in the first chapter it summarized an introduction to the principles and challenges for the multimedia transmission over packet networks. The most recent advances in video compression technologies are detailed in the second chapter, focusing in particular on aspects that involve the resilience to packet loss impairments. The third chapter deals with the main techniques adopted to protect the multimedia flow for mitigating the packet loss corruption due to channel failures. The fourth chapter introduces the more recent advances in network adaptive media transport detailing the techniques that prioritize the video packet flow. The fifth chapter makes a literature review of the existing distortion estimation techniques focusing mainly on their limitation aspects. The second part of the thesis describes the original results obtained in the modelling of the video distortion deriving from the transmission over an error prone network. In particular, the sixth chapter presents three new distortion estimation algorithms able to estimate the video quality and shows the results of some validation tests performed to measure the accuracy of the employed algorithms. The seventh chapter proposes different application scenarios where the developed algorithms may be used to enhance quickly the video quality at the end user side. Finally, the eight chapter summarizes the thesis contributions and remarks the most important conclusions. It also derives some directions for future improvements. The intent of the entire work presented hereafter is to develop some video distortion estimation algorithms able to predict the user quality deriving from the loss on the network as well as providing the results of some useful applications able to enhance the user experience during a video streaming session.Questa tesi di dottorato affronta il problema della trasmissione efficiente di contenuti multimediali su reti a pacchetto inaffidabili e con limitate risorse di banda. L’obiettivo è quello di ideare alcuni algoritmi in grado di predire l’andamento della qualità del video ricevuto da un utente e successivamente ideare alcune tecniche in grado di migliorare l’esperienza dell’utente finale nella fruizione dei servizi video. In particolare i contributi originali del presente lavoro riguardano lo sviluppo di algoritmi per la stima della distorsione e l’ideazione di alcuni scenari applicativi in molto frequenti dove poter valutare i benefici ottenibili applicando gli algoritmi di stima. I contributi presentati in questa tesi di dottorato sono il risultato degli studi compiuti con il gruppo di Telecomunicazioni del Dipartimento di Elettrotecnica Elettronica ed Informatica (DEEI) dell’Università degli Studi di Trieste durante il corso di dottorato in Ingegneria dell’Informazione. Negli ultimi anni la multimedialità, diffusa sulle reti cablate e wireless, sta diventando parte integrante del modo di utilizzare la rete diventando di fatto il fenomeno più imponente. Applicazioni come BitTorrent, la condivisione di file musicali e multimediali e il podcasting ad esempio costituiscono una parte significativa del traffico attuale su Internet. Quelle che negli ultimi anni erano le prime radio che trsmettevano sulla rete oggi si stanno evolvendo nei sistemi peer to peer per più avanzati per la diffusione della TV via web come CoolStreaming. Inoltre siti web come YouTube hanno costruito il loro business sulla memorizzazione/ distribuzione di video creati da chiunque abbia una semplice video camera. Un’altra caratteristica dell’imponente rivoluzione multimediale a cui stiamo assistendo è la diffusione dei video anche all’interno delle case dove i contenuti multimediali vengono distribuiti mediante delle reti wireless locali tra i vari dispositivi finali. Tutt’oggi è in corso una rivoluzione della multimedialità sulle reti IP con le radio, i televisioni, la telefonia e tutti i video che devono essere distribuiti sulle reti cablate e wireless verso utenti eterogenei. In generale la gran parte delle applicazioni multimediali richiedono una banda elevata e dei ritardi molto contenuti specialmente se le applicazioni sono di tipo interattivo. Sfortunatamente le reti wireless e Internet più in generale sono in grado di fornire un supporto limitato alle applicazioni multimediali. La variabilità di banda, di ritardo e nella perdita possono avere conseguenze gravi sulla qualità con cui viene ricevuto il video e questo può portare a una parziale insoddisfazione o addirittura alla rinuncia della fruizione da parte dell’utente finale. Le applicazioni multimediali sono spesso sensibili al ritardo e con requisiti di banda molto stringenti ma di fatto rimango tolleranti nei confronti delle perdite che possono avvenire durante la trasmissione. Al fine di superare le limitazioni è necessario sviluppare dei meccanismi di adattamento in grado di fare da ponte fra i requisiti delle applicazioni multimediali e le caratteristiche offerte dal livello di trasporto. Diversi approcci sono stati proposti in passato in letteratura per migliorare la trasmissione dei pacchetti riducendo le perdite; gli approcci variano dalle soluzioni di compressione efficiente all’aggiunta di ridondanza con tecniche di forward error correction e ritrasmissioni. Altre tecniche si basano sulla creazione di architetture di rete complesse in grado di garantire la QoS a livello rete dove router oppure altri agenti specializzati applicano diverse politiche di gestione del traffico in base ai valori contenuti nei campi dei pacchetti. Mediante queste architetture il traffico video viene marcato con delle classi di priorità al fine di creare una differenziazione nel traffico a livello rete; in particolare i pacchetti con i privilegi maggiori vengono assegnati alle classi di priorità più elevate e verranno persi con probabilità molto bassa mentre i pacchetti appartenenti alle classi di priorità inferiori saranno trattati alla stregua dei servizi di tipo best-effort. Uno dei principali problemi di questa soluzione riguarda come assegnare in maniera ottimale i singoli pacchetti video alle diverse classi di priorità. Un modo per effettuare questa classificazione è quello di procedere assegnando i pacchetti alle varie classi sulla base dell’importanza che ogni pacchetto ha sulla qualità finale. E’ stato dimostrato in numerosi lavori recenti che utilizzando come meccanismo per l’adattamento l’impatto sulla distorsione finale, porta significativi miglioramenti rispetto alle tecniche che utilizzano come parametro la sensibilità media del flusso nei confronti delle perdite. L’impatto che ogni pacchetto ha sulla qualità può essere espresso come la distorsione che viene introdotta al ricevitore se il pacchetto viene perso tenendo in considerazione gli effetti del recupero (error concealment) e la propagazione dell’errore (error propagation) caratteristica dei più recenti codificatori video. Gli algoritmi di stima della distorsione proposti in questa tesi sono in grado di riprodurre in maniera accurata l’inviluppo della distorsione derivante sia da perdite isolate che da perdite multiple nella rete con una complessità computazionale minima se confrontata con le più recenti tecniche di stima. Numerose prove sono stati effettuate al fine di validare gli algoritmi di stima e misurare l’influenza dei principali parametri di codifica e di decodifica. Al fine di enfatizzare i benefici ottenuti applicando gli algoritmi di stima della distorsione, durante la tesi verranno presentati alcuni scenari applicativi dove l’applicazione degli algoritmi proposti migliora sensibilmente la qualità finale percepita dagli utenti. Tali scenari verranno descritti, implementati e accuratamente valutati. In particolare, la distorsione stimata dal trasmettitore verrà incapsulata nei pacchetti video e, trasmessa nella rete dove agenti specializzati potranno agevolmente estrarla e utilizzarla come meccanismo rate-distortion per privilegiare alcuni pacchetti a discapito di altri. In particolare la struttura interna di un agente (un router) verrà modificata al fine di consentire la differenziazione del traffico utilizzando l’informazione dell’impatto che ogni pacchetto ha sulla qualità finale. I risultati ottenuti anche in termini di ridotta complessità computazionale in ogni scenario applicativo proposto mettono in luce i benefici derivanti dall’implementazione degli algoritmi di stima. La presenti tesi di dottorato è strutturata in due parti principali; la prima fornisce il background e rappresenta la base per tutti gli argomenti trattati nel seguito mentre la seconda parte è dedicata ai contributi originali e ai risultati ottenuti durante l’intera attività di ricerca. In riferimento alla prima parte in particolare un’introduzione ai principi e alle opportunità offerte dalla diffusione dei servizi multimediali sulle reti a pacchetto viene esposta nel primo capitolo. I progressi più recenti nelle tecniche di compressione video vengono esposti dettagliatamente nel secondo capitolo che si focalizza in particolare solo sugli aspetti che riguardano le tecniche per la mitigazione delle perdite. Il terzo capitolo introduce le principali tecniche per proteggere i flussi multimediali e ridurre le perdite causate dai fenomeni caratteristici del canale. Il quarto capitolo descrive i recenti avanzamenti nelle tecniche di network adaptive media transport illustrando i principali metodi utilizzati per differenziare il traffico video. Il quinto capitolo analizza i principali contributi nella letteratura sulle tecniche di stima della distorsione e si focalizza in particolare sulle limitazioni dei metodi attuali. La seconda parte della tesi descrive i contributi originali ottenuti nella modellizzazione della distorsione video derivante dalla trasmissione sulle reti con perdite. In particolare il sesto capitolo presenta tre nuovi algoritmi in grado di riprodurre fedelmente l’inviluppo della distorsione video. I numerosi test e risultati verranno proposti al fine di validare gli algoritmi e misurare l’accuratezza nella stima. Il settimo capitolo propone diversi scenari applicativi dove gli algoritmi sviluppati possono essere utilizzati per migliorare in maniera significativa la qualità percepita dall’utente finale. Infine l’ottavo capitolo sintetizza l’intero lavoro svolto e i principali risultati ottenuti. Nello stesso capitolo vengono inoltre descritti gli sviluppi futuri dell’attività di ricerca. L’obiettivo dell’intero lavoro presentato è quello di mostrare i benefici derivanti dall’utilizzo di nuovi algoritmi per la stima della distorsione e di fornire alcuni scenari applicativi di utilizzo.XIX Ciclo197

Design of a transport coding scheme for high-quality video over ATM networks

Caption title.Includes bibliographical references (p. 38-39).Supported by ARPA. F30602-92-C-0030 Supported by the Laboratory for Information and Decision Systems, Massachusetts Institute of Technology. DAAH04-95-1-0103V. Parthasarathy, J.W. Modestino and K.S. Vastola

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

Study and simulation of low rate video coding schemes

The semiannual report is included. Topics covered include communication, information science, data compression, remote sensing, color mapped images, robust coding scheme for packet video, recursively indexed differential pulse code modulation, image compression technique for use on token ring networks, and joint source/channel coder design

Investigating low-bitrate, low-complexity H.264 region of interest techniques in error-prone environments

The H.264/AVC video coding standard leverages advanced compression methods to provide a significant increase in performance over previous CODECs in terms of picture quality, bitrate, and flexibility. The specification itself provides several profiles and levels that allow customization through the use of various advanced features. In addition to these features, several new video coding techniques have been developed since the standard\u27s inception. One such technique known as Region of Interest (RoI) coding has been in existence since before H.264\u27s formalization, and several means of implementing RoI coding in H.264 have been proposed. Region of Interest coding operates under the assumption that one or more regions of a sequence have higher priority than the rest of the video. One goal of RoI coding is to provide a decrease in bitrate without significant loss of perceptual quality, and this is particularly applicable to low complexity environments, if the proper implementation is used. Furthermore, RoI coding may allow for enhanced error resilience in the selected regions if desired, making RoI suitable for both low-bitrate and error-prone scenarios. The goal of this thesis project was to examine H.264 Region of Interest coding as it applies to such scenarios. A modified version of the H.264 JM Reference Software was created in which all non-Baseline profile features were removed. Six low-complexity RoI coding techniques, three targeting rate control and three targeting error resilience, were selected for implementation. Error and distortion modeling tools were created to enhance the quality of experimental data. Results were gathered by varying a range of coding parameters including frame size, target bitrate, and macroblock error rates. Methods were then examined based on their rate-distortion curves, ability to achieve target bitrates accurately, and per-region distortions where applicable