Improved Side Information Generation for Distributed Video Coding by Exploiting Spatial and Temporal Correlations

Distributed Video Coding (DVC) is a new paradigm in video coding, which is receiving a lot of interests nowadays. Side Information (SI) generation is a key function in the DVC decoder, and plays a key-role in determining the performance of the codec. This paper proposes an improved motion compensated frame interpolation for SI generation in DVC, which exploits both spatial and temporal correlations in the sequences. Partially decoded Wyner-Ziv (WZ) frames, based on initial SI by motion compensated temporal interpolation, are exploited to improve the performance of the whole SI generation. More specifically, an enhanced temporal frame interpolation is proposed, including motion vector refinement and smoothing, optimal compensation mode selection, and a new matching criterion for motion estimation. The improved SI technique is also applied to a new hybrid spatial and temporal error concealment scheme to conceal errors in WZ frames, where the error-concealed results from spatial concealment are used to improve the performance of temporal concealment. Simulation results show that the proposed scheme can achieve up to 1.0 dB improvement in rate distortion performance in WZ frames for video with high motion, when compared to state-of-the-art DVC. In addition, both the objective and perceptual quality of the corrupted sequences are significantly improved by the proposed hybrid error concealment scheme, outperforming both spatial and temporal concealments alone

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

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

Distributed coding of endoscopic video

Triggered by the challenging prerequisites of wireless capsule endoscopic video technology, this paper presents a novel distributed video coding (DVC) scheme, which employs an original hash-based side-information creation method at the decoder. In contrast to existing DVC schemes, the proposed codec generates high quality side-information at the decoder, even under the strenuous motion conditions encountered in endoscopic video. Performance evaluation using broad endoscopic video material shows that the proposed approach brings notable and consistent compression gains over various state-of-the-art video codecs at the additional benefit of vastly reduced encoding complexity

An efficient error resilience scheme based on wyner-ziv coding for region-of-Interest protection of wavelet based video transmission

In this paper, we propose a bandwidth efficient error resilience scheme for wavelet based video transmission over wireless channel by introducing an additional Wyner-Ziv (WZ) stream to protect region of interest (ROI) in a frame. In the proposed architecture, the main video stream is compressed by a generic wavelet domain coding structure and passed through the error prone channel without any protection. Meanwhile, the predefined ROI area related wavelet coefficients obtained after an integer wavelet transform will be specially protected by WZ codec in an additional channel during transmission. At the decoder side, the error-prone ROI related wavelet coefficients will be used as side information to help decoding the WZ stream. Different size of WZ bit streams can be applied in order to meet different bandwidth condition and different requirement of end users. The simulation results clearly revealed that the proposed scheme has distinct advantages in saving bandwidth comparing with fully applied FEC algorithm to whole video stream and in the meantime offer the robust transmission over error prone channel for certain video applications

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

Intra-WZ quantization mismatch in distributed video coding

During the past decade, Distributed Video Coding (DVC) has emerged as a new video coding paradigm, shifting the complexity from the encoder-to the decoder-side. This paper addresses a problem of current DVC architectures that has not been studied in the literature so far, that is, the mismatch between the intra and Wyner-Ziv (WZ) quantization processes. Due to this mismatch, WZ rate is spent even for spatial regions that are accurately approximated by the side-information. As a solution, this paper proposes side-information generation using selective unidirectional motion compensation from temporally adjacent WZ frames. Experimental results show that the proposed approach yields promising WZ rate gains of up to 7% relative to the conventional method