Advanced side information creation techniques and framework for Wyner-Ziv video coding

Recently, several distributed video coding (DVC) solutions based on the distributed source coding (DSC) paradigm have appeared in the literature. Wyner-Ziv (WZ) video coding, a particular case of DVC where side information is made available at the decoder, enable to achieve a flexible distribution of the computational complexity between the encoder and decoder, promising to fulfill novel requirements from applications such as video surveillance, sensor networks and mobile camera phones. The quality of the side information at the decoder has a critical role in determining the WZ video coding rate-distortion (RD) performance, notably to raise it to a level as close as possible to the RD performance of standard predictive video coding schemes. Towards this target, efficient motion search algorithms for powerful frame interpolation are much needed at the decoder. In this paper, the RD performance of a Wyner-Ziv video codec is improved by using novel, advanced motion compensated frame interpolation techniques to generate the side information. The development of these type of side information estimators is a difficult problem in WZ video coding, especially because the decoder only has available some reference, decoded frames. Based on the regularization of the motion field, novel side information creation techniques are proposed in this paper along with a new frame interpolation framework able to generate higher quality side information at the decoder. To illustrate the RD performance improvements, this novel side information creation framework has been integrated in a transform domain turbo coding based Wyner-Ziv video codec. Experimental results show that the novel side information creation solution leads to better RD performance than available state-of-the-art side information estimators, with improvements up to 2 dB: moreover, it allows outperforming H.264/AVC Intra by up to 3 dB with a lower encoding complexity

Image Interpolation with Dense Disparity Estimation in Multiview Distributed Video Coding

This paper deals with the side information (SI) generation problem in multiview distributed video coding (MDVC). For inter-view interpolation, we propose a novel dense disparity estimation (DE) approach combined with a popular distributed video coding (DVC) technique. As disparity vectors are computed at the decoder side, and no coding rate is needed to transmit them, dense estimation techniques are made possible, leading to improved results without requiring high coding resources. Experimental results show that the proposed interpolation technique can achieve up to 2.0 dB improvement in SI reconstruction performance, when compared to state-of-the-art DVC techniques

Adaptive rounding operator for efficient Wyner-Ziv video coding

The research work disclosed in this publication is partially funded by the Strategic Educational Pathways Scholarship Scheme (Malta). The scholarship is part-financed by the European Union – European Social Fund. (ESF 1.25).The Distributed Video Coding (DVC) paradigm can theoretically reach the same coding efficiencies of predictive block-based video coding schemes, like H.264/AVC. However, current DVC architectures are still far from this ideal performance. This is mainly attributed to inaccuracies in the Side Information (SI) predicted at the decoder. The work in this paper presents a coding scheme which tries to avoid mismatch in the SI predictions caused by small variations in light intensity. Using the appropriate rounding operator for every coefficient, the proposed method significantly reduces the correlation noise between the Wyner-Ziv (WZ) frame and the corresponding SI, achieving higher coding efficiencies. Experimental results demonstrate that the average Peak Signal-to-Noise Ratio (PSNR) is improved by up to 0.56dB relative to the DISCOVER codec.peer-reviewe

Improving Turbo Codec Integration In Pixel-Domain Distributed Video Coding

The field of distributed video coding (DVC) theory has received a lot of attention in recent years and effective encoding techniques have been proposed. In the present work the framework of pixel domain Wyner-Ziv coding of video frames is considered, following the scheme proposed in A. Aaron et al. (2002). Some key frames are supposed to be available at the decoder while other frames are Wyner-Ziv encoded using turbo codes; at the decoder motion compensated interpolation between the key frames is performed in order to construct the side information for the Wyner-Ziv frame decoding. In this paper an improved model for the correlation noise between the side information frame and the original one is proposed. It is shown that modeling the nonstationary nature of the noise leads to substantial gain in the rate-distortion performance. Furthermore, by considering the memory of the noise, we show that some further gain can be obtained by placing an interleaver before the turbo codec so as to spread the correlation noise all over the fram

Side Information Generation in Distributed Video Coding

Distributed Video Coding (DVC) coding paradigm is based largely on two theorems of Information Theory and Coding, which are Slepian-wolf theorem and Wyner-Ziv theorem that were introduced in 1973 and 1976 respectively. DVC bypasses the need of performing Motion Compensation (MC) and Motion Estimation (ME) which are largely responsible for the complex encoder in devices. DVC instead relies on exploiting the source statistics, totally/partially, at only the decoder. Wyner-Ziv coding, a particular case of DVC, which is explored in detail in this thesis. In this scenario, two correlated sources are independently encoded, while the encoded streams are decoded jointly at the single decoder exploiting the correlation between them. Although the distributed coding study dates back to 1970’s, but the practical efforts and developments in the field began only last decade. Upcoming applications (like those of video surveillance, mobile camera, wireless sensor networks) can rely on DVC, as they don’t have high computational capabilities and/or high storage capacity. Current coding paradigms, MPEG-x and H.26x standards, predicts the frame by means of Motion Compensation and Motion Estimation which leads to highly complex encoder. Whilst in WZ coding, the correlation between temporally adjacent frames is performed only at the decoder, which results in fairly low complex encoder. The main objective of the current thesis is to investigate for an improved scheme for Side Information (SI) generation in DVC framework. SI frames, available at the decoder are generated through the means of Radial Basis Function Network (RBFN) neural network. Frames are estimated from decoded key frames block-by-block. RBFN network is trained offline using training patterns from different frames collected from standard video sequences

Practical Distributed Video Coding in Packet Lossy Channels

Improving error resilience of video communications over packet lossy channels is an important and tough task. We present a framework to optimize the quality of video communications based on distributed video coding (DVC) in practical packet lossy network scenarios. The peculiar characteristics of DVC indeed require a number of adaptations to take full advantage of its intrinsic robustness when dealing with data losses of typical real packet networks. This work proposes a new packetization scheme, an investigation of the best error-correcting codes to use in a noisy environment, a practical rate-allocation mechanism, which minimizes decoder feedback, and an improved side-information generation and reconstruction function. Performance comparisons are presented with respect to a conventional packet video communication using H.264/advanced video coding (AVC). Although currently the H.264/AVC rate-distortion performance in case of no loss is better than state-of-the-art DVC schemes, under practical packet lossy conditions, the proposed techniques provide better performance with respect to an H.264/AVC-based system, especially at high packet loss rates. Thus the error resilience of the proposed DVC scheme is superior to the one provided by H.264/AVC, especially in the case of transmission over packet lossy networks

Selective reconstruction of low motion regions in distributed video coding

The research work disclosed in this publication is partially funded by the Strategic Educational Pathways Scholarship Scheme (Malta). The scholarship is part-financed by the European Union - European Social Fund. (ESF 1.25).The Distributed Video Coding (DVC) paradigm offers lightweight encoding capabilities which are suitable for devices with limited computational resources. Moreover, DVC techniques can theoretically achieve the same coding efficiency as the traditional video coding schemes which employ more complex encoders. However, the performance of practical DVC architectures is still far from such theoretical bounds, mainly due to the inaccurate Side Information (SI) predicted at the decoder. The work presented in this paper shows that the soft-input values predicted at the decoder may not correctly predict the Wyner-Ziv coefficients, even for regions containing low motion. This generally degrades compression efficiency. To mitigate this, the proposed system predicts the quality of the SI for regions with low motion and then employs a technique which avoids correcting mismatch at locations where the SI and WZ falls within different quantization intervals but the prediction error is within an acceptable range. The experimental results demonstrate that the average Peak Signal-to-Noise Ratio (PSNR) is improved by up to 0.39dB compared to the state-of-the-art DVC architectures, like the DISCOVER codec.peer-reviewe

Improving the Rate-Distortion Performance in Distributed Video Coding

Distributed video coding is a coding paradigm, which allows encoding of video frames at a complexity that is substantially lower than that in conventional video coding schemes. This feature makes it suitable for some emerging applications such as wireless surveillance video and mobile camera phones. In distributed video coding, a subset of frames in the video sequence, known as the key frames, are encoded using a conventional intra-frame encoder, such as H264/AVC in the intra mode, and then transmitted to the decoder. The remaining frames, known as the Wyner-Ziv frames, are encoded based on the Wyner-Ziv principle by using the channel codes, such as LDPC codes. In the transform-domain distributed video coding, each Wyner-Ziv frame undergoes a 4x4 block DCT transform and the resulting DCT coefficients are grouped into DCT bands. The bitplaines corresponding to each DCT band are encoded by a channel encoder, for example an LDPCA encoder, one after another. The resulting error-correcting bits are retained in a buffer at the encoder and transmitted incrementally as needed by the decoder. At the decoder, the key frames are first decoded. The decoded key frames are then used to generate a side information frame as an initial estimate of the corresponding Wyner-Ziv frame, usually by employing an interpolation method. The difference between the DCT band in the side information frame and the corresponding one in the Wyner-Ziv frame, referred to as the correlation noise, is often modeled by Laplacian distribution. A soft-input information for each bit in the bitplane is obtained using this correlation noise model and the corresponding DCT band of the side information frame. The channel decoder then uses this soft-input information along with some error-correcting bits sent by the encoder to decode the bitplanes of each DCT band in each of the Wyner-Ziv frames. Hence, an accurate estimation of the correlation noise model parameter(s) and generation of high-quality side information are required for reliable soft-input information for the bitplanes in the decoder, which in turn leads to a more efficient decoding. Consequently, less error-correcting bits need to be transmitted from the encoder to the decoder to decode the bitplanes, leading to a better compression efficiency and rate-distortion performance. The correlation noise is not stationary and its statistics vary within each Wyner-Ziv frame and within its corresponding DCT bands. Hence, it is difficult to find an accurate model for the correlation noise and estimate its parameters precisely at the decoder. Moreover, in existing schemes the parameters of the correlation noise for each DCT band are estimated before the decoder starts to decode the bitplanes of that DCT band and they are not modified and kept unchanged during decoding process of the bitplanes. Another problem of concern is that, since side information frame is generated in the decoder using the temporal interpolation between the previously decoded frames, the quality of the side information frames is generally poor when the motions between the frames are non-linear. Hence, generating a high-quality side information is a challenging problem. This thesis is concerned with the study of accurate estimation of correlation noise model parameters and increasing in the quality of the side information from the standpoint of improving the rate-distortion performance in distributed video coding. A new scheme is proposed for the estimation of the correlation noise parameters wherein the decoder decodes simultaneously all the bitplanes of a DCT band in a Wyner-Ziv frame and then refines the parameters of the correlation noise model of the band in an iterative manner. This process is carried out on an augmented factor graph using a new recursive message passing algorithm, with the side information generated and kept unchanged during the decoding of the Wyner-Ziv frame. Extensive simulations are carried out showing that the proposed decoder leads to an improved rate-distortion performance in comparison to the original DISCOVER codec and in another DVC codec employing side information frame refinement, particularly for video sequences with high motion content. In the second part of this work, a new algorithm for the generation of the side information is proposed to refine the initial side information frame using the additional information obtained after decoding the previous DCT bands of a Wyner-Ziv frame. The simulations are carried out demonstrating that the proposed algorithm provides a performance superior to that of schemes employing the other side information refinement mechanisms. Finally, it is shown that incorporating the proposed algorithm for refining the side information into the decoder proposed in the first part of the thesis leads to a further improvement in the rate-distortion performance of the DVC codec

Wavelet based distributed video coding with spatial scalability

In this paper, an improved spatial scalable wavelet domain distributed video coding (DVC) scheme is proposed. In this scheme, we adaptively apply differential pulse code modulation (DPCM) Wyner-Ziv (WZ) coding and discrete cosine transform (DCT) based intra block coding to reduced-resolution layer. Due to the low energy nature of high-pass subbands, WZ coding can be directly used. At decoder, in full-resolution layer WZ frame decoding, an efficient side information (SI) generation technique for low-pass subband is proposed, in which motion compensated interpolation (MCI) is performed on full-resolution signal. On the other hand, a refined technique is also employed to generate the SI for high-pass subbands by taking advantage of inter-band correlation. Experimental results show that the proposed scheme provides an efficient wavelet domain DVC coding paradigm. ?2008 IEEE.EI