A Novel Multiple Description Approach to Predictive Video Coding

Multiple description coding (MDC) is a source coding technique that exploits path diversity to solve packet losses over error-prone channels. In this paper, we propose an improved drift-free multi-state MDC method based on H.264/AVC coding scheme. At the encoder side, we compress original video into multiple independent H.264 streams with different coding parameters, which can help us to control correlations between the descriptions. At the decoder side, each description is considered as a noisy observation of the original video, and a linear minimum mean square error (LMMSE) based merge algorithm is proposed to combine the descriptions. Experimental results show that the proposed algorithm can achieve better coding efficiency and visual quality than temporary MDC present in [1]. The error resilience ability is also improved by the fact that each frame is coded twice with different parameters.

Multiple description coding (MDC) is a source coding technique that exploits path diversity to increase the robustness of transmitting a compressed signal over error-prone channels. However, the application of MDC to video coding is still problematic because a prediction mismatch problem, called drift, may occur at the decoder when one description is lost. In the literature, it has been shown that drift can be effectively prevented by encoding this prediction mismatch and sending it as side information in a three-prediction-loop structure. However, this side information is totally redundant when both descriptions are received. We propose a very simple, but efficient two-stage MDC in the central prediction loop based on the three-prediction-loop structure of A. Reibman et al. (see Proc. IEEE Int. Conf. Image Processing - ICIP'99, p.837-41, 1999). We introduce an additional multiple description scalar quantizer into the central prediction loop. The encoding of the side information is modified in such a way that it can be used to improve the video quality when no drift occurs, but still maintain a drift prevention capability. The simulation results, with different video sequences at various packet loss rates, demonstrate that the proposed two-stage MDC structure indeed enhances the quality when the channel is error-free, yet effectively avoids drift when one description is completely lost.

Multiple-description coding (MDC) is a source coding technique which provides an effective way to mitigate the effects of packet errors/loses by making use of multiple channels. The most attractive application of MDC is perhaps the multiple-description video coding (MDVC) in the peer-to-peer (P2P) scenario so as to support simultaneous video streaming to a large population of clients. To this end, a number of MDVC schemes (both non-scalable and scalable) have been proposed in the past few years. However, almost all non-scalable schemes would suffer from the prediction mismatch between the references used at the encoder and decoder sides (for motion compensation); whereas most scalable schemes (involving a base-layer and some enhancement layers) would suffer from the inter-dependency within the enhancement-layer information. In this paper, we keep a common base-layer in all descriptions and propose some novel design of multiple-description scalar quantizer (MDSQ) that is applied on the enhancement-layer. As a result, this scheme can overcome the above drawbacks and more importantly achieve the seamless streaming among all peers.

Multiple description coding (MDC) is a source coding technique that exploits path diversity to increase the robustness of transmitting a compressed signal over error-prone channels. However, the applicant of MDC to video coding is still problematic because a prediction mismatch problem, called drift, may occur at the decoder when one description is lost. In this paper, we propose a drift free motion-compensated predictive coding method for multiple description scalar quantizers. The proposed method maintains two more prediction loops at the encoder side to produce all possible predictions. Then, the two descriptions are generated from these two additional prediction loops in such a way that the drift can be prevented when only one description is received. By receiving both descriptions, the decoder can still combine these two descriptions in the central prediction loop to improve the video quality. Experimental results show that the proposed method can effectively prevent drift and improve the quality of single-description reconstruction by 0.2-0.8 dB as compared to the method in [A. Reibman et al., 1999].

In view of perfect compatibility with the standard source and channel codec, temporal sampling-based multiple description coding (MDC) has become a better choice for practical applications. However, for the frames change from one scene to another temporal correlation may be destroyed by temporal sampling extremely, which results in the false estimation when the related frames are lost at the side decoder. Therefore, in this article the frames containing scene change are detected and duplicated before temporal sampling, which maintains better temporal correlation in each description. Furthermore, for better rate distortion performance temporal sampling is employed adaptively, that is, frame skipping or up-sampling according to the motion characteristics in original video. The experimental results exhibit better performance of the proposed scheme than other schemes whether in the on–off MDC environment or packet lossy network, especially about 15 dB improvements for the frames with scene change. Therefore, it may be a promising choice for video transmission over error-prone channels, especially over wireless networks.

In this chapter, we introduce novel algorithms for constructing multiple multicast tree and assigning multiple description (MD) video to a group of heterogeneous multicast destinations. Our main objective is to increase the number of assigned MD video to each destination node. In order to achieve our objective, we propose to employ the independent-description property of MDC (multiple description coding) along with multiple multicast tree. We mean by independent-description property of MDC the following. If there are three video descriptions, for example, then receiving any subset of video descriptions, i.e., ({VD1,VD2,VD3} ,{VD1,VD2} ,{VD1,VD3} ,{VD2,VD3} ,{VD1} ,{VD2} ,{VD3}) of the video descriptions will reproduce the original video in different qualities depending on the number of video descriptions received. A main issue of video multicasting for heterogeneous destinations is the assignment of video descriptions and the construction of multicast trees. However, the assignment of MD video and the construction of multicast tree can greatly affect the user satisfaction (i.e., affect the number of assigned video description to each destination and hence affect the quality of the received video. However, many questions are raised: How multiple multicast tree should be constructed? And how MD video should be assigned? Is it better to construct multiple multicast tree first and then assign the video descriptions? Or is it better to assign the video descriptions first and we then construct multiple multicast tree? Should we perform that in a distributed manner or in a centralized one? Does the independent-description of MDC increase the user satisfaction? To answer these questions, we propose different algorithms to construct multiple multicast tree and to assign MD video. The proposed algorithms are: Serial MDC, Distributed MDC, Centralized MDC, and sequential MDC. Serial MDC algorithm constructs multiple paths, to each destination, and assigns a different video description to each of them. After that, it constructs multiple multicast tree based on the assignment of MD video. Distributed MDC algorithm assigns MD video and constructs multiple multicast tree in parallel and in distributed fashion. In Centralized MDC, the assignment of MD video and the construction of multiple multicast tree are performed in a centralized manner. However, Centralized MDC first constructs multiple multicast tree and then assigns different video description to each multicast tree. Finally, Sequential MDC sequntially assigns MD video to each multicast tree.This means that all destinations should be assigned the first description. Then, 17

Providing reliable video communications over wireless ad-hoc networks is becoming increasingly important as these networks become widely employed in military, homeland defense security, and disaster recovery applications. However, wireless ad-hoc networks have a dynamically changing topology that can cause failures of links and nodes, thus resulting in path loss. Additionally, video communications over wireless ad-hoc networks can suffer from noise and fading effects in the channel. Therefore, it is important to provide error resilience for reliable video communications over such an error-prone network. A number of solutions have been proposed for this problem, including source coding diversity and multipath routing. Source coding diversity methods such as multiple description coding (MDC) have proven to be effective for robust video communications, especially when combined with network path diversity (Gogate et al., 2002; Mao et al., 2003; Apostolopoulos & Trott, 2004). We investigate new MDC methods combined with path diversity to enhance the error resilience of video communications over wireless ad hoc networks. The basic idea of MDC is to encode the video sequence into several descriptions for transmission over multiple paths. Each description can be independently decoded and combined with the other descriptions to provide an acceptable video quality. When more descriptions are received for reconstruction, higher video quality can be achieved. As long as all descriptions are not lost simultaneously, somewhat acceptable quality can be maintained. In order to reduce the likelihood of simultaneous loss of descriptions, different descriptions are transmitted through different paths. This is referred as MDC with path diversity, which reduces the possibility of simultaneous loss of different descriptions and enables load balancing in networks. Many MDC algorithms have been proposed (Goyal, 2001) and they can be divided into three categories: subsampling algorithms in the temporal (Apostolopoulos, 2001), spatial (Franchi et al., 2005) or frequency domain (Reibman et al., 2001), multiple description quantization algorithms (Vaishampayan, 1993; Dumitrescu & Wu, 2009), and multiple description transform coding (Wang et al., 2001). Wang, Reibman & Lin (2005) provides a good review for MDC algorithms. Since subsampling methods are easy to implement and compatible with different video standards, they have been the most commonly investigated MDC algorithms. These methods generally work in the spatial, temporal, or frequency domain to generate multiple 3

Multiple description coding (MDC) is a well-known robust data compression algorithm designed to minimize the distortion caused by data loss in packet-based communication systems. Several MDC schemes for transmitting wavelet compressed images have been developed. However, these MDC schemes cannot be adopted for digital mobile wireless applications where both packet loss and bit error are present, because individual description in these MDC schemes usually does not have adequate error resilience capability to combat the bit error in transmission. In this paper, we propose an algorithm to achieve robust communication over error prone transmission channels with both packet loss and bit error. We integrate the multiple description scalar quantization (MDSQ) with the multiple wavelet tree image coding method in order to provide an excellent error resilient capability. Two descriptions are generated independently by using index assignment of MDSQ. For each description, multiple sub-sampling is applied to split the wavelet coefficients of the source image into multiple sub-sources. Each sub-source is then entropy coded using the SPIHT algorithm and followed by a channel coding scheme that combines cyclic redundancy code (CRC) and rate compatible punctured convolutional (RCPC) code to offer unequal error protection to the entropy coded bits. The unequal error protection channel coding rate is designed based on the bit error sensitivity of different bit planes to achieve maximum end-to-end quality of service. Experimental results show that the proposed scheme not only exhibits an excellent error resilient performance but also demonstrates graceful degradation over error prone channels with changing rate of packet loss and bit error.

Multiple description (MD) coding is a promising alternative for the robust transmission of information over error-prone channels. In 3D image technology, the depth map represents the distance between the camera and objects in the scene. Using the depth map combined with the existing multiview image, it can be efficient to synthesize images of any virtual viewpoint position, which can display more realistic 3D scenes. Differently from the conventional 2D texture image, the depth map contains a lot of spatial redundancy information, which is not necessary for view synthesis, but may result in the waste of compressed bits, especially when using MD coding for robust transmission. In this paper, we focus on the redundancy removal of MD coding based on the DCT (discrete cosine transform) domain. In view of the characteristics of DCT coefficients, at the encoder, a Lagrange optimization approach is designed to determine the amounts of high frequency coefficients in the DCT domain to be removed. It is noted considering the low computing complexity that the entropy is adopted to estimate the bit rate in the optimization. Furthermore, at the decoder, adaptive zero-padding is applied to reconstruct the depth map when some information is lost. The experimental results have shown that compared to the corresponding scheme, the proposed method demonstrates better rate central and side distortion performance.

Multiple description coding (MDC) has been proposed as a source coding technique that is robust to channel errors for video transmission. MDC generates multiple independent bit-streams, where the multiple bit-streams are referred to as multiple descriptions (MD). Furthermore, it enables a useful reproduction of the signal when any description is received correctly. This paper proposes a new multicast heuristic algorithm, that attempts to take the benefit of MDC properties and multiple paths, to improve the user's satisfaction for a group of heterogeneous destinations in wireless ad hoc network. Extensive simulations clearly demonstrate the effectiveness of the proposed algorithm in improving the user's satisfaction irrespective of the number of destinations in the multicast group.

With the advances of digital video technology and the rapid growth of the Internet and wireless networks, video communication has been gaining in importance. Emerging applications includes: video conferencing, digital video broadcasting, peer-to-peer video transmission, etc. Extensive works on the Internet routing algorithms as well as the video coding techniques have been conducted to provide reliable video transmis-sion over error-prone environments. Multiple description coding (MDC) has emerged as a promising approach to combat packet losses and enhance error-concealment in video transmission. By using MDC, a video sequence is encoded into multiple independently decodable descrip-tions. As more descriptions are received at the decoder, the reconstructed video with better quality is obtained. These multiple description streams are transmitted along multiple paths to provide reliable transmission over packet-networks. The efficiency of an MDC scheme depends on the way of introducing redundancy into individual descriptions. An H.264/AVC-based multiple description video coding scheme is proposed. The proposed MDC scheme utilizes the advanced video coding tools and features pro-vided in H.264/AVC, including slice groups, variable block-size motion compensation, and multiple reference frames. Slice groups are adopted to produce multiple descrip-tions. Spatial and temporal correlations between neighboring macroblocks in video frames are exploited to achieve efficient redundancy coding. From the experimental results, the proposed MDC scheme has superior rate-distortion (R-D) performance to previous slice-group based MDC scheme. A complete error-concealment mechanism is also supported by the proposed MDC scheme to handle packet losses. Combined with the current Internet routing algorithms, e.g. an over-lay network, the proposed MDC scheme is capable of providing a practical solution for video transmission.

Multiple description coding (MDC) is a source coding technique that involves coding the source information into multiple descriptions. When these descriptions are transmitted over different channels in packet network or error-prone wireless environment, graceful degradation can be achieved even if part of descriptions are not received by the receiver. When MDC is applied to wavelet subband based image coding, it is possible to introduce correlation between the descriptions in each subband. In this paper, we consider using such a correlation as well as potentially error corrupted description as side information in the decoding to formulate the MDC decoding as a Wyner Ziv decoding problem. If only part of descriptions is lost, however, their correlation information is still available. Therefore, the proposed Wyner Ziv decoder can recover the description by using the correlation information and the error corrupted description as side information. High quality reconstruction can still be obtained by combining the decoded descriptions from Wyner Ziv decoder. The proposed scheme takes advantage of an efficient way to use the correlation information, thus makes the system more robust to channel error corruption. Experimental result shows that, comparing to conventional multiple description wavelet based image coding, the PSNR of the received and decoded image could be improved noticeably when coding at the same bit rate.

Multiple-description coding (MDC) provides an effective way to mitigate the effects of packet errors/loses by making use of multiple channels. Perhaps, the most attractive application of MDC is in the peer-to-peer (P2P) scenario to support simultaneous video streaming to a large population of clients. To this end, a number of multiple-description video coding (MDVC) schemes (both non-scalable and scalable) were proposed in the past few years. However, almost all non-scalable schemes would suffer from the prediction mismatch between the references used at the encoder and decoder sides; whereas all scalable schemes (involving a base-layer and some enhancement layers) would suffer from the inter-dependency within the enhancement-layer information. In this paper, we propose a transform-domain MDVC method that can solve these problems and at the same time offer some other interesting features.

Multiple distribution trees and multiple description (MD) coding are highly robust since they provide redundancy both in network paths and data. However, MD coded streaming includes a redundant information, which results in additional bandwidth consumptions in entire distribution trees. In this paper, we deploy core nodes in distribution tree, and give a role of MD coding to each core node, instead of a source node then we show how amount of bandwidth consumption can be reduced. Since the problem of finding an optimal set of core nodes is proved to be NP-hard, an intuitional heuristic-based algorithm is proposed. The simulation results show that our heuristic algorithm reduces the bandwidth consumptions by about 25% in the hierarchical topology compared to the MD coding in source node only.

Multiple description (MD) coding is a source coding technique for information transmission over unreliable networks. In MD coding, the coder generates several different descriptions of the same signal and the decoder can produce a useful reconstruction of the source with any received subset of these descriptions. In this paper, we study the problem of MD coding of stationary Gaussian sources with memory. First, we compute an approximate MD rate distortion region for these sources, which we prove to be asymptotically tight at high rates. This region generalizes the MD rate distortion region of El Gamal and Cover (1982), and Ozarow (1980) for memoryless Gaussian sources. Then, we develop an algorithm for the design of optimal two-channel biorthogonal filter banks for MD coding of Gaussian sources. We show that optimal filters are obtained by allocating the redundancy over frequency with a reverse "water-filling" strategy. Finally, we present experimental results which show the effectiveness of our filter banks in the low complexity, low rate regime.