An enhanced reconstruction algorithm for unidirectional Distributed Video Coding

Distributed Video Coding (DVC) is an emerging video coding technology that utilizes the distributed source coding principles to build very low cost video encoders, yet with remarkable error resilience. In the common DVC framework, the reconstruction function plays a vital role that has a direct impact on the output video quality. In this paper, a novel algorithm is proposed for the reconstruction function, particularly focusing on the unidirectional DVC architecture. The proposed technique exploits the variations of the bit error rate of the Wyner-Ziv decoded bit stream and the side information stream. The simulation results show that the proposed algorithm yields a significant improvement of the objective and subjective video quality at no additional bit rate cost

Towards practical distributed video coding

Multimedia is increasingly becoming a utility rather than mere entertainment. The range of video applications has increased, some of which are becoming indispensable in modem lifestyle. Video surveillance is one area that has attracted significant amount of focus and also benefited from considerable research effort for development. However, it is noted that there is still a notable technological gap between an ideal video surveillance platform and the available solutions, mainly in the form of the encoder and decoder complexity balance and the associated design costs. In this thesis, we tocus on an emerging technology, Distributed Video Coding (DVC), which is ideally suited for the video surveillance scenario, and fits many other potential applications too.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Advanced distributed video coding techniques

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

REGION-BASED ADAPTIVE DISTRIBUTED VIDEO CODING CODEC

The recently developed Distributed Video Coding (DVC) is typically suitable for the applications where the conventional video coding is not feasible because of its inherent high-complexity encoding. Examples include video surveillance usmg wireless/wired video sensor network and applications using mobile cameras etc. With DVC, the complexity is shifted from the encoder to the decoder. The practical application of DVC is referred to as Wyner-Ziv video coding (WZ) where an estimate of the original frame called "side information" is generated using motion compensation at the decoder. The compression is achieved by sending only that extra information that is needed to correct this estimation. An error-correcting code is used with the assumption that the estimate is a noisy version of the original frame and the rate needed is certain amount of the parity bits. The side information is assumed to have become available at the decoder through a virtual channel. Due to the limitation of compensation method, the predicted frame, or the side information, is expected to have varying degrees of success. These limitations stem from locationspecific non-stationary estimation noise. In order to avoid these, the conventional video coders, like MPEG, make use of frame partitioning to allocate optimum coder for each partition and hence achieve better rate-distortion performance. The same, however, has not been used in DVC as it increases the encoder complexity. This work proposes partitioning the considered frame into many coding units (region) where each unit is encoded differently. This partitioning is, however, done at the decoder while generating the side-information and the region map is sent over to encoder at very little rate penalty. The partitioning allows allocation of appropriate DVC coding parameters (virtual channel, rate, and quantizer) to each region. The resulting regions map is compressed by employing quadtree algorithm and communicated to the encoder via the feedback channel. The rate control in DVC is performed by channel coding techniques (turbo codes, LDPC, etc.). The performance of the channel code depends heavily on the accuracy of virtual channel model that models estimation error for each region. In this work, a turbo code has been used and an adaptive WZ DVC is designed both in transform domain and in pixel domain. The transform domain WZ video coding (TDWZ) has distinct superior performance as compared to the normal Pixel Domain Wyner-Ziv (PDWZ), since it exploits the ' spatial redundancy during the encoding. The performance evaluations show that the proposed system is superior to the existing distributed video coding solutions. Although the, proposed system requires extra bits representing the "regions map" to be transmitted, fuut still the rate gain is noticeable and it outperforms the state-of-the-art frame based DVC by 0.6-1.9 dB. The feedback channel (FC) has the role to adapt the bit rate to the changing ' statistics between the side infonmation and the frame to be encoded. In the unidirectional scenario, the encoder must perform the rate control. To correctly estimate the rate, the encoder must calculate typical side information. However, the rate cannot be exactly calculated at the encoder, instead it can only be estimated. This work also prbposes a feedback-free region-based adaptive DVC solution in pixel domain based on machine learning approach to estimate the side information. Although the performance evaluations show rate-penalty but it is acceptable considering the simplicity of the proposed algorithm. vii

Motion Scalability for Video Coding with Flexible Spatio-Temporal Decompositions

PhDThe research presented in this thesis aims to extend the scalability range of the wavelet-based video coding systems in order to achieve fully scalable coding with a wide range of available decoding points. Since the temporal redundancy regularly comprises the main portion of the global video sequence redundancy, the techniques that can be generally termed motion decorrelation techniques have a central role in the overall compression performance. For this reason the scalable motion modelling and coding are of utmost importance, and specifically, in this thesis possible solutions are identified and analysed. The main contributions of the presented research are grouped into two interrelated and complementary topics. Firstly a flexible motion model with rateoptimised estimation technique is introduced. The proposed motion model is based on tree structures and allows high adaptability needed for layered motion coding. The flexible structure for motion compensation allows for optimisation at different stages of the adaptive spatio-temporal decomposition, which is crucial for scalable coding that targets decoding on different resolutions. By utilising an adaptive choice of wavelet filterbank, the model enables high compression based on efficient mode selection. Secondly, solutions for scalable motion modelling and coding are developed. These solutions are based on precision limiting of motion vectors and creation of a layered motion structure that describes hierarchically coded motion. The solution based on precision limiting relies on layered bit-plane coding of motion vector values. The second solution builds on recently established techniques that impose scalability on a motion structure. The new approach is based on two major improvements: the evaluation of distortion in temporal Subbands and motion search in temporal subbands that finds the optimal motion vectors for layered motion structure. Exhaustive tests on the rate-distortion performance in demanding scalable video coding scenarios show benefits of application of both developed flexible motion model and various solutions for scalable motion coding

The cerebellum linearly encodes whisker position during voluntary movement

Active whisking is an important model sensorimotor behavior, but the function of the cerebellum in the rodent whisker system is unknown. We have made patch clamp recordings from Purkinje cells in vivo to identify whether cerebellar output encodes kinematic features of whisking including the phase and set point. We show that Purkinje cell spiking activity changes strongly during whisking bouts. On average, the changes in simple spike rate coincide with or slightly precede movement, indicating that the synaptic drive responsible for these changes is predominantly of efferent (motor) rather than re-afferent (sensory) origin. Remarkably, on-going changes in simple spike rate provide an accurate linear read-out of whisker set point. Thus, despite receiving several hundred thousand discrete synaptic inputs across a non-linear dendritic tree, Purkinje cells integrate parallel fiber input to generate precise information about whisking kinematics through linear changes in firing rate

Scalable Video Coding

International audienceWith the evolution of Internet to heterogeneous networks both in terms of processing power and network bandwidth, different users demand the different versions of the same content. This has given birth to the scalable era of video content where a single bitstream contains multiple versions of the same video content which can be different in terms of resolutions, frame rates or quality. Several early standards, like MPEG2 video, H.263, and MPEG4 part II already include tools to provide different modalities of scalability. However, the scalable profiles of these standards are seldom used. This is because the scalability comes with significant loss in coding efficiency and the Internet was at its early stage. Scalable extension of H.264/AVC is named scalable video coding and is published in July 2007. It has several new coding techniques developed and it reduces the gap of coding efficiency with state-of-the-art non-scalable codec while keeping a reasonable complexity increase. After an introduction to scalable video coding, we present a proposition regarding the scalable functionality of H.264/AVC, which is the improvement of the compression ratio in enhancement layers (ELs) of subband/wavelet based scalable bitstream. A new adaptive scanning methodology for intra frame scalable coding framework based on subband/wavelet coding approach is presented for H.264/AVC scalable video coding. It takes advantage of the prior knowledge of the frequencies which are present in different higher frequency subbands. Thus, by just modification of the scan order of the intra frame scalable coding framework of H.264/AVC, we can get better compression, without any compromise on PSNR

Depth measurement in integral images.

The development of a satisfactory the three-dimensional image system is a constant pursuit of the scientific community and entertainment industry. Among the many different methods of producing three-dimensional images, integral imaging is a technique that is capable of creating and encoding a true volume spatial optical model of the object scene in the form of a planar intensity distribution by using unique optical components. The generation of depth maps from three-dimensional integral images is of major importance for modern electronic display systems to enable content-based interactive manipulation and content-based image coding. The aim of this work is to address the particular issue of analyzing integral images in order to extract depth information from the planar recorded integral image. To develop a way of extracting depth information from the integral image, the unique characteristics of the three-dimensional integral image data have been analyzed and the high correlation existing between the pixels at one microlens pitch distance interval has been discovered. A new method of extracting depth information from viewpoint image extraction is developed. The viewpoint image is formed by sampling pixels at the same local position under different micro-lenses. Each viewpoint image is a two-dimensional parallel projection of the three-dimensional scene. Through geometrically analyzing the integral recording process, a depth equation is derived which describes the mathematic relationship between object depth and the corresponding viewpoint images displacement. With the depth equation, depth estimation is then converted to the task of disparity analysis. A correlation-based block matching approach is chosen to find the disparity among viewpoint images. To improve the performance of the depth estimation from the extracted viewpoint images, a modified multi-baseline algorithm is developed, followed by a neighborhood constraint and relaxation technique to improve the disparity analysis. To deal with the homogenous region and object border where the correct depth estimation is almost impossible from disparity analysis, two techniques, viz. Feature Block Pre-selection and “Consistency Post-screening, are further used. The final depth maps generated from the available integral image data have achieved very good visual effects