Enhanced Inter-Prediction Via Shifting Transformation in the H.264/AVC

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Distributed video coding for wireless video sensor networks: a review of the state-of-the-art architectures

Distributed video coding (DVC) is a relatively new video coding architecture originated from two fundamental theorems namely, Slepian–Wolf and Wyner–Ziv. Recent research developments have made DVC attractive for applications in the emerging domain of wireless video sensor networks (WVSNs). This paper reviews the state-of-the-art DVC architectures with a focus on understanding their opportunities and gaps in addressing the operational requirements and application needs of WVSNs

Motion compensation with minimal residue dispersion matching criteria

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Tecnoloigia, 2016.Com a crescente demanda por serviços de vídeo, técnicas de compressão de vídeo tornaram-se uma tecnologia de importância central para os sistemas de comunicação modernos. Padrões para codificação de vídeo foram criados pela indústria, permitindo a integração entre esses serviços e os mais diversos dispositivos para acessá-los. A quase totalidade desses padrões adota um modelo de codificação híbrida, que combina métodos de codificação diferencial e de codificação por transformadas, utilizando a compensação de movimento por blocos (CMB) como técnica central na etapa de predição. O método CMB tornou-se a mais importante técnica para explorar a forte redundância temporal típica da maioria das sequências de vídeo. De fato, muito do aprimoramento em termos de e ciência na codificação de vídeo observado nas últimas duas décadas pode ser atribuído a refinamentos incrementais na técnica de CMB. Neste trabalho, apresentamos um novo refinamento a essa técnica. Uma questão central à abordagem de CMB é a estimação de movimento (EM), ou seja, a seleção de vetores de movimento (VM) apropriados. Padrões de codificação tendem a regular estritamente a sintaxe de codificação e os processos de decodificação para VM's e informação de resíduo, mas o algoritmo de EM em si é deixado a critério dos projetistas do codec. No entanto, embora praticamente qualquer critério de seleção permita uma decodi cação correta, uma seleção de VM criteriosa é vital para a e ciência global do codec, garantindo ao codi cador uma vantagem competitiva no mercado. A maioria do algoritmos de EM baseia-se na minimização de uma função de custo para os blocos candidatos a predição para um dado bloco alvo, geralmente a soma das diferenças absolutas (SDA) ou a soma das diferenças quadradas (SDQ). A minimização de qualquer uma dessas funções de custo selecionará a predição que resulta no menor resíduo, cada uma em um sentido diferente porém bem de nido. Neste trabalho, mostramos que a predição de mínima dispersão de resíduo é frequentemente mais e ciente que a tradicional predição com resíduo de mínimo tamanho. Como prova de conceito, propomos o algoritmo de duplo critério de correspondência (ADCC), um algoritmo simples em dois estágios para explorar ambos esses critérios de seleção em turnos. Estágios de minimização de dispersão e de minimização de tamanho são executadas independentemente. O codificador então compara o desempenho dessas predições em termos da relação taxa-distorção e efetivamente codifica somente a mais eficiente. Para o estágio de minimização de dispersão do ADCC, propomos ainda o desvio absoluto total com relação à média (DATM) como a medida de dispersão a ser minimizada no processo de EM. A tradicional SDA é utilizada como a função de custo para EM no estágio de minimização de tamanho. O ADCC com SDA/DATM foi implementado em uma versão modificada do software de referência JM para o amplamente difundido padrão H.264/AVC de codificação. Absoluta compatibilidade a esse padrão foi mantida, de forma que nenhuma modificação foi necessária no lado do decodificador. Os resultados mostram aprimoramentos significativos com relação ao codificador H.264/AVC não modificado.With the ever growing demand for video services, video compression techniques have become a technology of central importance for communication systems. Industry standards for video coding have emerged, allowing the integration between these services and the most diverse devices. The almost entirety of these standards adopt a hybrid coding model combining di erential and transform coding methods, with block-based motion compensation (BMC) at the core of its prediction step. The BMC method have become the single most important technique to exploit the strong temporal redundancy typical of most video sequences. In fact, much of the improvements in video coding e ciency over the past two decades can be attributed to incremental re nements to the BMC technique. In this work, we propose another such re nement. A key issue to the BMC framework is motion estimation (ME), i.e., the selection of appropriate motion vectors (MV). Coding standards tend to strictly regulate the coding syntax and decoding processes for MV's and residual information, but the ME algorithm itself is left at the discretion of the codec designers. However, though virtually any MV selection criterion will allow for correct decoding, judicious MV selection is critical to the overall codec performance, providing the encoder with a competitive edge in the market. Most ME algorithms rely on the minimization of a cost function for the candidate prediction blocks given a target block, usually the sum of absolute di erences (SAD) or the sum of squared di erences (SSD). The minimization of any of these cost functions will select the prediction that results in the smallest residual, each in a di erent but well de ned sense. In this work, we show that the prediction of minimal residue dispersion is frequently more e cient than the usual prediction of minimal residue size. As proof of concept, we propose the double matching criterion algorithm (DMCA), a simple two-pass algorithm to exploit both of these MV selection criteria in turns. Dispersion minimizing and size minimizing predictions are carried out independently. The encoder then compares these predictions in terms of rate-distortion performance and outputs only the most e cient one. For the dispersion minimizing pass of the DMCA, we also propose the total absolute deviation from the mean (TADM) as the measure of residue dispersion to be minimized in ME. The usual SAD is used as the ME cost function in the size minimizing pass. The DMCA with SAD/TADM was implemented in a modi ed version of the JM reference software encoder for the widely popular H.264/AVC coding standard. Absolute compliance to the standard was maintained, so that no modi cations on the decoder side were necessary. Results show signi cant improvements over the unmodi ed H.264/AVC encoder

Complexity adaptation in video encoders for power limited platforms

With the emergence of video services on power limited platforms, it is necessary to consider both performance-centric and constraint-centric signal processing techniques. Traditionally, video applications have a bandwidth or computational resources constraint or both. The recent H.264/AVC video compression standard offers significantly improved efficiency and flexibility compared to previous standards, which leads to less emphasis on bandwidth. However, its high computational complexity is a problem for codecs running on power limited plat- forms. Therefore, a technique that integrates both complexity and bandwidth issues in a single framework should be considered. In this thesis we investigate complexity adaptation of a video coder which focuses on managing computational complexity and provides significant complexity savings when applied to recent standards. It consists of three sub functions specially designed for reducing complexity and a framework for using these sub functions; Variable Block Size (VBS) partitioning, fast motion estimation, skip macroblock detection, and complexity adaptation framework. Firstly, the VBS partitioning algorithm based on the Walsh Hadamard Transform (WHT) is presented. The key idea is to segment regions of an image as edges or flat regions based on the fact that prediction errors are mainly affected by edges. Secondly, a fast motion estimation algorithm called Fast Walsh Boundary Search (FWBS) is presented on the VBS partitioned images. Its results outperform other commonly used fast algorithms. Thirdly, a skip macroblock detection algorithm is proposed for use prior to motion estimation by estimating the Discrete Cosine Transform (DCT) coefficients after quantisation. A new orthogonal transform called the S-transform is presented for predicting Integer DCT coefficients from Walsh Hadamard Transform coefficients. Complexity saving is achieved by deciding which macroblocks need to be processed and which can be skipped without processing. Simulation results show that the proposed algorithm achieves significant complexity savings with a negligible loss in rate-distortion performance. Finally, a complexity adaptation framework which combines all three techniques mentioned above is proposed for maximizing the perceptual quality of coded video on a complexity constrained platform

Novel VLSI Architecture for Quantization and Variable Length Coding for H-264/AVC Video Compression Standard

Integrated multimedia systems process text, graphics, and other discrete media such as digital audio and video streams. In an uncompressed state, graphics, audio and video data, especially moving pictures, require large transmission and storage capacities which can be very expensive. Hence video compression has become a key component of any multimedia system or application. The ITU (International Telecommunications Union) and MPEG (Moving Picture Experts Group) have combined efforts to put together the next generation of video compression standard, the H.264/MPEG-4 PartlO/AVC, which was finalized in 2003. The H.264/AVC uses significantly improved and computationally intensive compression techniques to maximize performance. H.264/AVC compliant encoders achieve the same reproduction quality as encoders that are compliant with the previous standards while requiring 60% or less of the bit rate [2]. This thesis aims at designing two basic blocks of an ASIC capable of performing the H.264 video compression. These two blocks, the Quantizer, and Entropy Encoder implement the Baseline Profile of the H.264/AVC standard. The architecture is implemented in Register Transfer Level HDL and synthesized with Synopsys Design Compiler using TSMC 0.25(xm technology, giving us an estimate of the hardware requirements in real-time implementation. The quantizer block is capable of running at 309MHz and has a total area of 785K gates with a power requirement of 88.59mW. The entropy encoder unit is capable of running at 250 MHz and has a total area of 49K gates with a power requirement of 2.68mW. The high speed that is achieved in this thesis simply indicates that the two blocks Quantizer and Entropy Encoder can be used as IP embedded in the HDTV systems

Efficient Motion Estimation and Mode Decision Algorithms for Advanced Video Coding

H.264/AVC video compression standard achieved significant improvements in coding efficiency, but the computational complexity of the H.264/AVC encoder is drastically high. The main complexity of encoder comes from variable block size motion estimation (ME) and rate-distortion optimized (RDO) mode decision methods. This dissertation proposes three different methods to reduce computation of motion estimation. Firstly, the computation of each distortion measure is reduced by proposing a novel two step edge based partial distortion search (TS-EPDS) algorithm. In this algorithm, the entire macroblock is divided into different sub-blocks and the calculation order of partial distortion is determined based on the edge strength of the sub-blocks. Secondly, we have developed an early termination algorithm that features an adaptive threshold based on the statistical characteristics of rate-distortion (RD) cost regarding current block and previously processed blocks and modes. Thirdly, this dissertation presents a novel adaptive search area selection method by utilizing the information of the previously computed motion vector differences (MVDs). In H.264/AVC intra coding, DC mode is used to predict regions with no unified direction and the predicted pixel values are same and thus smooth varying regions are not well de-correlated. This dissertation proposes an improved DC prediction (IDCP) mode based on the distance between the predicted and reference pixels. On the other hand, using the nine prediction modes in intra 4x4 and 8x8 block units needs a lot of overhead bits. In order to reduce the number of overhead bits, an intra mode bit rate reduction method is suggested. This dissertation also proposes an enhanced algorithm to estimate the most probable mode (MPM) of each block. The MPM is derived from the prediction mode direction of neighboring blocks which have different weights according to their positions. This dissertation also suggests a fast enhanced cost function for mode decision of intra encoder. The enhanced cost function uses sum of absolute Hadamard-transformed differences (SATD) and mean absolute deviation of the residual block to estimate distortion part of the cost function. A threshold based large coefficients count is also used for estimating the bit-rate part

Adaptive mode decision with residual motion compensation for distributed video coding

Distributed video coding (DVC) is a coding paradigm that entails low complexity encoding by exploiting the source statistics at the decoder. To improve the DVC coding efficiency, this paper presents a novel adaptive technique for mode decision to control and take advantage of skip mode and intra mode in DVC initially proposed by Luong et al. in 2013. The adaptive mode decision (AMD) is not only based on quality of key frames but also the rate of Wyner-Ziv (WZ) frames. To improve noise distribution estimation for a more accurate mode decision, a residual motion compensation is proposed to estimate a current noise residue based on a previously decoded frame. The experimental results, integrating AMD in two efficient DVC codecs, show that the proposed AMD DVC significantly improves the rate distortion performance without increasing the encoding complexity. For a GOP size of 2 on the set of six test sequences, the average (Bjontegaard) bitrate saving of the proposed codec is 35.5. on WZ frames compared with the DISCOVER codec. This saving is mainly achieved by AMD

Selected topics on distributed video coding

Distributed Video Coding (DVC) is a new paradigm for video compression based on the information theoretical results of Slepian and Wolf (SW), and Wyner and Ziv (WZ). While conventional coding has a rigid complexity allocation as most of the complex tasks are performed at the encoder side, DVC enables a flexible complexity allocation between the encoder and the decoder. The most novel and interesting case is low complexity encoding and complex decoding, which is the opposite of conventional coding. While the latter is suitable for applications where the cost of the decoder is more critical than the encoder's one, DVC opens the door for a new range of applications where low complexity encoding is required and the decoder's complexity is not critical. This is interesting with the deployment of small and battery-powered multimedia mobile devices all around in our daily life. Further, since DVC operates as a reversed-complexity scheme when compared to conventional coding, DVC also enables the interesting scenario of low complexity encoding and decoding between two ends by transcoding between DVC and conventional coding. More specifically, low complexity encoding is possible by DVC at one end. Then, the resulting stream is decoded and conventionally re-encoded to enable low complexity decoding at the other end. Multiview video is attractive for a wide range of applications such as free viewpoint television, which is a system that allows viewing the scene from a viewpoint chosen by the viewer. Moreover, multiview can be beneficial for monitoring purposes in video surveillance. The increased use of multiview video systems is mainly due to the improvements in video technology and the reduced cost of cameras. While a multiview conventional codec will try to exploit the correlation among the different cameras at the encoder side, DVC allows for separate encoding of correlated video sources. Therefore, DVC requires no communication between the cameras in a multiview scenario. This is an advantage since communication is time consuming (i.e. more delay) and requires complex networking. Another appealing feature of DVC is the fact that it is based on a statistical framework. Moreover, DVC behaves as a natural joint source-channel coding solution. This results in an improved error resilience performance when compared to conventional coding. Further, DVC-based scalable codecs do not require a deterministic knowledge of the lower layers. In other words, the enhancement layers are completely independent from the base layer codec. This is called the codec-independent scalability feature, which offers a high flexibility in the way the various layers are distributed in a network. This thesis addresses the following topics: First, the theoretical foundations of DVC as well as the practical DVC scheme used in this research are presented. The potential applications for DVC are also outlined. DVC-based schemes use conventional coding to compress parts of the data, while the rest is compressed in a distributed fashion. Thus, different conventional codecs are studied in this research as they are compared in terms of compression efficiency for a rich set of sequences. This includes fine tuning the compression parameters such that the best performance is achieved for each codec. Further, DVC tools for improved Side Information (SI) and Error Concealment (EC) are introduced for monoview DVC using a partially decoded frame. The improved SI results in a significant gain in reconstruction quality for video with high activity and motion. This is done by re-estimating the erroneous motion vectors using the partially decoded frame to improve the SI quality. The latter is then used to enhance the reconstruction of the finally decoded frame. Further, the introduced spatio-temporal EC improves the quality of decoded video in the case of erroneously received packets, outperforming both spatial and temporal EC. Moreover, it also outperforms error-concealed conventional coding in different modes. Then, multiview DVC is studied in terms of SI generation, which differentiates it from the monoview case. More specifically, different multiview prediction techniques for SI generation are described and compared in terms of prediction quality, complexity and compression efficiency. Further, a technique for iterative multiview SI is introduced, where the final SI is used in an enhanced reconstruction process. The iterative SI outperforms the other SI generation techniques, especially for high motion video content. Finally, fusion techniques of temporal and inter-view side informations are introduced as well, which improves the performance of multiview DVC over monoview coding. DVC is also used to enable scalability for image and video coding. Since DVC is based on a statistical framework, the base and enhancement layers are completely independent, which is an interesting property called codec-independent scalability. Moreover, the introduced DVC scalable schemes show a good robustness to errors as the quality of decoded video steadily decreases with error rate increase. On the other hand, conventional coding exhibits a cliff effect as the performance drops dramatically after a certain error rate value. Further, the issue of privacy protection is addressed for DVC by transform domain scrambling, which is used to alter regions of interest in video such that the scene is still understood and privacy is preserved as well. The proposed scrambling techniques are shown to provide a good level of security without impairing the performance of the DVC scheme when compared to the one without scrambling. This is particularly attractive for video surveillance scenarios, which is one of the most promising applications for DVC. Finally, a practical DVC demonstrator built during this research is described, where the main requirements as well as the observed limitations are presented. Furthermore, it is defined in a setup being as close as possible to a complete real application scenario. This shows that it is actually possible to implement a complete end-to-end practical DVC system relying only on realistic assumptions. Even though DVC is inferior in terms of compression efficiency to the state of the art conventional coding for the moment, strengths of DVC reside in its good error resilience properties and the codec-independent scalability feature. Therefore, DVC offers promising possibilities for video compression with transmission over error-prone environments requirement as it significantly outperforms conventional coding in this case