L’utilisation de plusieurs cœurs pour l’exécution des applications mobiles sera l’approche dominante dans les systèmes embarqués pour les prochaines années. Cette approche permet en générale d’augmenter les performances du système sans augmenter la vitesse de l’horloge. Grâce à cela, la consommation d’énergie reste modérée. Toutefois, la concurrence entre les tâches doit être exploitée afin d’améliorer les performances du système dans les différentes situations où l’application peut s’exécuter. Les applications multimédias comme la vidéoconférence ou la vidéo haute définition, ont de nombreuses nouvelles fonctionnalités qui nécessitent des calculs complexes par rapport aux normes précédentes de codage vidéo. Ces applications créent une charge de travail très importante sur les systèmes multiprocesseurs. L’exploitation du parallélisme pour les applications multimédia, comme le codec vidéo H.264/AVC, peut se faire à différents niveaux : au niveau de données ou bien au niveau tâches. Dans le cadre de cette thèse de doctorat, nous proposons de nouvelles solutions pour une meilleure exploitation du parallélisme dans les applications multimédia sur des systèmes embarqués ayant une architecture parallèle symétrique (ou SMP pour Symmetric Multi-Processor). Des approches innovantes pour le décodeur H.264/AVC qui traitent des composantes de couleur et des blocs de l’image en parallèle sont proposées et expérimentées. / Parallel computing is currently the dominating architecture in embedded systems. Concurrency improves the performance of the system rather without increasing the clock speed which affects the power consumption of the system. However, concurrency needs to be exploited in order to improve the system performance in different applications environments. Multimedia applications (real-Time conversational services such as video conferencing, video phone, etc.) have many new features that require complex computations compared to previous video coding standards. These applications have a challenging workload for future multiprocessors. Exploiting parallelism in multimedia applications can be done at data and functional levels or using different instruction sets and architectures. In this research, we design new parallel algorithms and mapping methodologies in order to exploit the natural existence of parallelism in multimedia applications, specifically the H.264/AVC video decoder. We mainly target symmetric shared-Memory multiprocessors (SMPs) for embedded devices such as ARM Cortex-A9 multicore chips. We evaluate our novel parallel algorithms of the H.264/AVC video decoder on different levels: memory load, energy consumption, and execution time.

Today, eavesdropping is becoming a common issue in the rapidly growing digital network and has foreseen the need for secret communication channels embedded in digital media. In this paper, a novel steganography technique designed for Standard Definition Digital Television (SDTV) H.264/AVC encoded video sequences is presented. The algorithm introduced here makes use of the compression properties of the Context Adaptive Variable Length Coding (CAVLC) entropy encoder to achieve a low complexity and real-time inserting method. The chosen scheme hides the private message directly in the H.264/AVC bit stream by modifying the AC frequency quantized residual luminance coefficients of intrapredicted I-frames. In order to avoid error propagation in adjacent blocks, an interlaced embedding strategy is applied. Likewise, the steganography technique proposed allows self-detection of the hidden message at the target destination. The code source was implemented by mixing MATLAB 2010 b and Java development environments. Finally, experimental results have been assessed through objective and subjective quality measures and reveal that less visible artifacts are produced with the technique proposed by reaching PSNR values above 40.0 dB and an embedding bit rate average per secret communication channel of 425 bits/sec. This exemplifies that steganography is affordable in digital television.

Video codec compresses the input video source to reduce storage and transmission bandwidth requirements while maintaining the quality. It is an essential technology for applications, to name a few such as digital television, DVD-Video, mobile TV, videoconferencing and internet video streaming. There are different video codecs used in the industry today and understanding their operation to target certain video applications is the key to optimization. The latest advanced video codec standards have become of great importance in multimedia industries which provide cost-effective encoding and decoding of video and contribute for high compression and efficiency. Currently, H.264 AVC, AVS, and DIRAC are used in the industry to compress video. H.264 codec standard developed by the ITU-T Video Coding Experts Group (VCEG) together with the ISO/IEC Moving Picture Experts Group (MPEG). Audio-video coding standard (AVS) is a working group of audio and video coding standard in China. VC-2, also known as Dirac Pro developed by BBC, is a royalty free technology that anyone can use and has been standardized through the SMPTE as VC-2. H.264 AVC, Dirac Pro, Dirac and AVS-P2 are dedicated to High Definition Video, while AVS-P7 is to mobile video. Out of many standards, this work performs a comparative analysis for the H.264 AVC, DIRAC PRO/SMPTE-VC-2 and AVS-P7 standards in low bitrate region and high bitrate region. Bitrate control and constant QP are the methods which are employed for analysis. Evaluation parameters like Compression Ratio, PSNR and SSIM are used for quality comparison. Depending on target application and available bitrate, order of performance is mentioned to show the preferred codec.

The current trend of digital convergence creates the need for the video encoder and decoder system, known as codec in short, that should support multiple video standards on a single platform. In a modern video codec, quantization is a key unit used for video compression. In this thesis, a generalized quantization algorithm and hardware implementation is presented to compute quantized coefficient for six different video codecs including the new developing codec High Efficiency Video Coding (HEVC). HEVC, successor to H.264/MPEG-4 AVC, aims to substantially improve coding efficiency compared to AVC High Profile. The thesis presents a high performance circuit shared architecture that can perform the quantization operation for HEVC, H.264/AVC, AVS, VC-1, MPEG- 2/4 and Motion JPEG (MJPEG). Since HEVC is still in drafting stage, the architecture was designed in such a way that any final changes can be accommodated into the design. The proposed quantizer architecture is completely division free as the division operation is replaced by multiplication, shift and addition operations. The design was implemented on FPGA and later synthesized in CMOS 0.18 μm technology. The results show that the proposed design satisfies the requirement of all codecs with a maximum decoding capability of 60 fps at 187.3 MHz for Xilinx Virtex4 LX60 FPGA of a 1080p HD video. The scheme is also suitable for low-cost implementation in modern multi-codec systems.

Video codec compresses the input video source to reduce storage and transmission bandwidth requirements while maintaining the quality. It is an essential technology for applications, to name a few such as digital television, DVD-Video, mobile TV, videoconferencing and internet video streaming. There are different video codecs used in the industry today and understanding their operation to target certain video applications is the key to optimization. The latest advanced video codec standards have become of great importance in multimedia industries which provide cost-effective encoding and decoding of video and contribute for high compression and efficiency. Currently, H.264 AVC, AVS, and DIRAC are used in the industry to compress video. H.264 codec standard developed by the ITU-T Video Coding Experts Group (VCEG) together with the ISO/IEC Moving Picture Experts Group (MPEG). Audio-video coding standard (AVS) is a working group of audio and video coding standard in China. VC-2, also known as Dirac Pro developed by BBC, is a royalty free technology that anyone can use and has been standardized through the SMPTE as VC-2. H.264 AVC, Dirac Pro, Dirac and AVS-P2 are dedicated to High Definition Video, while AVS-P7 is to mobile video. Out of many standards, this work performs a comparative analysis for the H.264 AVC, DIRAC PRO/SMPTE-VC-2 and AVS-P7 standards in low bitrate region and high bitrate region. Bitrate control and constant QP are the methods which are employed for analysis. Evaluation parameters like Compression Ratio, PSNR and SSIM are used for quality comparison. Depending on target application and available bitrate, order of performance is mentioned to show the preferred codec.

A novel residual prediction algorithm is proposed for high-bit-rate video coding in this work. We analysis the relationship between the residual data and different quantization parameters, according to the comparison results, we observe that the residual data is raised rapidly when the quality increases. Consequently, in order to reduce the bitrate, we propose a new residual prediction algorithm, it mainly reduce the residual data when the quantization parameter is finer. The proposed algorithm not only reduces the bitrate but also improves the video quality for high-bit-rate coding. Experimental results show that the proposed algorithm outperforms H.264/AVC. Compared to H.264/AVC, the proposed method decreases about 9.66% bitrate in average. The experimental results demonstrated that the second-order-residual prediction algorithm is efficiency for high-bit-rate coding.

H.264/AVC intra prediction method is an efficient tool to reduce spatial redundancies by using multidirectional spatial prediction modes. In this paper, a novel intra prediction method is designed to improve coding efficiency. Firstly, we propose a direction-distance oriented prediction which considers the distance between the predict value and the reference samples according to the direction of the prediction modes. Secondly, we apply the concept of image restoration by using the projections onto convex sets (POCS) to intra prediction which uses adaptively filtering based on the surrounding reconstructed pixel to predict blocks. The experimental results show that the average bit-rate reduction of 0.75% and PSNR gain improved of 0.119dB are achieved.

With the rapid growth of video services on smartphones such as video conferencing, video telephone and WebTV, implementation of video compression on mobile terminal becomes extremely important. However, the low computation capability of mobile devices becomes a bottleneck which calls for low complexity techniques for video coding. This work presents two set of algorithms for reducing the complexity of motion estimation. Binary motion estimation techniques using one-bit and two-bit transforms reduce the computational complexity of matching error criterion, however sometimes generate inaccurate motion vectors. The first set includes two neighborhood matching based algorithms which attempt to reduce computations to only a fraction of other methods. Simulation results demonstrate that full search local binary pattern (FS-LBP) algorithm reconstruct visually more accurate frames compared to full search algorithm (FSA). Its reduced complexity LBP (RC-LBP) version decreases computations significantly to only a fraction of the other methods while maintaining acceptable performance. The second set introduces edge detection approach for partial distortion elimination based on binary patterns. Spiral partial distortion elimination (SpiralPDE) has been proposed in literature which matches the pixel-to-pixel distortion in a predefined manner. Since, the contribution of all the pixels to the distortion function is different, therefore, it is important to analyze and extract these cardinal pixels. The proposed algorithms are called lossless fast full search partial distortion elimination ME based on local binary patterns (PLBP) and lossy edge-detection pixel decimation technique based on local binary patterns (ELBP). PLBP reduces the matching complexity by matching more contributable pixels early by identifying the most diverse pixels in a local neighborhood. ELBP captures the most representative pixels in a block in order of contribution to the distortion function by evaluating whether the individual pixels belong to the edge or background. Experimental results demonstrate substantial reduction in computational complexity of ELBP with only a marginal loss in prediction quality.

With the rapid growth of video services on smartphones such as video conferencing, video telephone and WebTV, implementation of video compression on mobile terminal becomes extremely important. However, the low computation capability of mobile devices becomes a bottleneck which calls for low complexity techniques for video coding. This work presents two set of algorithms for reducing the complexity of motion estimation. Binary motion estimation techniques using one-bit and two-bit transforms reduce the computational complexity of matching error criterion, however sometimes generate inaccurate motion vectors. The first set includes two neighborhood matching based algorithms which attempt to reduce computations to only a fraction of other methods. Simulation results demonstrate that full search local binary pattern (FS-LBP) algorithm reconstruct visually more accurate frames compared to full search algorithm (FSA). Its reduced complexity LBP (RC-LBP) version decreases computations significantly to only a fraction of the other methods while maintaining acceptable performance. The second set introduces edge detection approach for partial distortion elimination based on binary patterns. Spiral partial distortion elimination (SpiralPDE) has been proposed in literature which matches the pixel-to-pixel distortion in a predefined manner. Since, the contribution of all the pixels to the distortion function is different, therefore, it is important to analyze and extract these cardinal pixels. The proposed algorithms are called lossless fast full search partial distortion elimination ME based on local binary patterns (PLBP) and lossy edge-detection pixel decimation technique based on local binary patterns (ELBP). PLBP reduces the matching complexity by matching more contributable pixels early by identifying the most diverse pixels in a local neighborhood. ELBP captures the most representative pixels in a block in order of contribution to the distortion function by evaluating whether the individual pixels belong to the edge or background. Experimental results demonstrate substantial reduction in computational complexity of ELBP with only a marginal loss in prediction quality.

Multiterminal (MT) video coding is a practical application of the MT source coding theory. For MT source coding theory, two problems associated with achievable rate regions are well investigated into in this thesis: a new sufficient condition for BT sum-rate tightness, and the sum-rate loss for quadratic Gaussian MT source coding. Practical code design for ideal Gaussian sources with quadratic distortion measure is also achieved for cases more than two sources with minor rate loss compared to theoretical limits. However, when the theory is applied to practical applications, the performance of MT video coding has been unsatisfactory due to the difficulty to explore the correlation between different camera views. In this dissertation, we present an MT video coding scheme under the H.264/AVC framework. In this scheme, depth camera information can be optionally sent to the decoder separately as another source sequence. With the help of depth information at the decoder end, inter-view correlation can be largely improved and thus so is the compression performance. With the depth information, joint estimation from decoded frames and side information at the decoder also becomes available to improve the quality of reconstructed video frames. Experimental result shows that compared to separate encoding, up to 9.53% of the bit rate can be saved by the proposed MT scheme using decoder depth information, while up to 5.65% can be saved by the scheme without depth camera information. Comparisons to joint video coding schemes are also provided.