<title>Embedded wavelet video coding with error concealment</title>

Error concealment is a well-known technique to improve reproduced picture quality in cases which parts of the coded picture are not available at a decoder for reconstruction. The conventional error concealment methods generally make use of the correlation between a damaged marcoblock and its adjacent macroblocks in the same frame and/or the previous frame. However, performance results of concealment methods are different each other and dependent on how much damaged frames and macroblocks are correlated to surrounding ones temporally and spatially. Moreover, most of them can not conceal effectively the consecutively damaged frames or macro blocks caused by wireless bursty packet loss features, since motion vectors and correlation information between the damaged images are already destroyed. The proposed error concealment aware error resilient video coding is a new method which has an intelligent error concealment selector by using pre-estimation technique of the possibly damaged motion vectors at the encoder. The method recommends the best error concealment per macroblock by transmitting additionally its error concealment selection codes to the decoder. The chosen error concealment helps to conceal the damaged MB at the decoder even when losses of frames are bursty. The experimental results show the substantial effectiveness to improve video quality at the cost of a little bit overhead at the transmitted bit streams.

The problem of error control and concealment in video communication is becoming increasingly important because of the growing interest in video delivery over unreliable channels such as wireless networks and the Internet. This paper reviews the techniques that have been developed for error control and concealment. These techniques are described in three categories according to the roles that the encoder and decoder play in the underlying approaches. Forward error concealment includes methods that add redundancy at the source end to enhance error resilience of the coded bit streams. Error concealment by postprocessing refers to operations at the decoder to recover the damaged areas based on characteristics of image and video signals. Last, interactive error concealment covers techniques that are dependent on a dialogue between the source and destination. Both current research activities and practice in international standards are covered.

Video transmission over wireless packet networks is gaining importance due to the concept of universal personal communication. Further, it is considered an important step towards wireless multimedia. The challenge however is to achieve good video quality over mobile channels, where typically the channel conditions vary due to signal fading. Hence this paper investigates adaptive rate controlled video transmission for robust video communication under packet wireless environment. A combination of mobile and an ATM backbone network is assumed in this work. An error resilient design for the video coder, as proposed in Rajugopal et al. (1996) is employed here. This video coder comprises wavelet transform (WT), multi-resolution motion estimation (MRME) and a robust design for zero tree quantization. Two configurations, one employing MRME and the other using 1D-WT for temporal analysis, are considered for the video coder. Adaptive dynamic rate control is required to adapt the video communication to the channel conditions. It provides more channel protection when the channel is severe and improves the source rate and hence the performance when the conditions are favorable. An algorithm for dynamic rate control under varying channel conditions is proposed in this paper. It is evaluated under narrowband and broadband channel conditions. From the results, it is concluded that the dynamic rate control is very effective in optimizing the quality under varying mobile channel conditions. It was observed that the dynamic rate control provides at least an acceptable video quality under severe channel conditions and a good video quality when the channel conditions are favorable.

In this paper, auto regressive (AR) model is applied to error concealment for block-based packet video coding. In the proposed error concealment scheme, the motion vector for each corrupted block is first derived by any kind of recovery algorithms. Then each pixel within the corrupted block is replenished as the weighted summation of pixels within a square centered at the pixel indicated by the derived motion vector in a regression manner. Two block-dependent AR coefficient derivation algorithms under spatial and temporal continuity constraints are proposed respectively. The first one derives the AR coefficients via minimizing the summation of the weighted square errors within all the available neighboring blocks under the spatial continuity constraint. The confidence weight of each pixel sample within the available neighboring blocks is inversely proportional to the distance between the sample and the corrupted block. The second one derives the AR coefficients by minimizing the summation of the weighted square errors within an extended block in the previous frame along the motion trajectory under the temporal continuity constraint. The confidence weight of each extended sample is inversely proportional to the distance toward the corresponding motion aligned block whereas the confidence weight of each sample within the motion aligned block is set to be one. The regression results generated by the two algorithms are then merged to form the ultimate restorations. Various experimental results demonstrate that the proposed error concealment strategy is able to improve both the objective and subjective quality of the replenished blocks compared to other methods.

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.

As the newest video coding standard, H.264/AVC adopts the high-efficiently predictive coding and variable length entropy coding to achieve high compression efficiency. On the other side, transmission errors become the major problem faced by video broadcasting service providers. Error concealment (EC) here is adopted to handle slices with huge conjunctive corrupted areas inside. Considering error propagation from corrupted slice to succeeding ones is the key factor affecting the video quality, this paper proposes a novel temporal EC scheme including the bi-direction motion vector (MV) retrieval method and an adaptive EC ordering basing on it. Background and motional steady shift part of slice will be given top and second priority, respectively. Combined with our proposed improved boundary matching algorithm (IBMA) which provides more accurate distortion function, experiments results show that our proposal achieves better performance under different error rate channel, compared with EC algorithm adopted in H.264 reference software.

In this paper, a large capacity of data hiding algorithm was proposed for H.264/AVC, with lower bit-rate can be achieved in the mean while. The main idea is to hide the information into appropriately selected motion vectors in Inter frames, we modulate LSB bit of the x and y sub-components of each MVD data to hide 2 bits information, in this way we can exploit the large hiding capacity as well as the lower bit-rate increase. The data can be extracted just by decoding part of the motion vector difference and do not need the original video stream, which meets the requirement of the modern detection of real-time perfectly. Simulation results show that the algorithm can achieve a great embedding capability as well as the slight bit-rate increase and visual distortion.

Motion-vector-based error concealment algorithms recover lost blocks by motion compensation with the estimated motion vectors. Traditionally, the estimated motion vectors for the lost block are derived by the direct usage of the neighboring available motion vectors. In this work, the residual signal in a block encoded in the video bitstream is used to measure the reliability of the corresponding motion vector. The residual information is applied to weight the neighboring available motion vectors differently, to further improve a newly proposed mathematical formulation between encoded motion vectors and extrapolated motion vectors. The proposed error concealment method using the residual information outperforms a state-of-the-art error concealment algorithm by up to 2.12 dB in sequence PSNR, and outperforms a classic DMVE method by up to 8.27 dB.

We propose an error concealment method for robust video transmission based on watermarking technique. In this method, the motion vector information is used as the watermark and embedded in the transform coefficients before quantization. A proper embedding algorithm is designed with the characteristics of the video coder taken into consideration, so that the embedding watermark has little influence on the video quality and the coding efficiency. At the decoder, the extracted watermark is used to effectively detect errors and restore the corrupted motion vectors. Then the restored motion vectors are utilized in error concealment. Simulation results demonstrate the advantages of the proposed method in error prone environment. The proposed method is applicable to all the block-transform based video coding schemes.

Error protection and concealment of motion vectors are of prime concern when video is transmitted over variable-bandwidth error-prone channels, such as wireless channels. In this paper, we investigate the influence of corrupted motion vectors in video coding based on motion-compensated temporal filtering, and develop various error protection and concealment mechanisms for this class of codecs. The experimental results show that our proposed motion vector coding technique significantly increases the robustness against transmission errors and generates performance gains of up to 7 dB compared with the original coding technique at the cost of less than 4% in terms of rate. It is also shown that our proposed spatial error-concealment mechanism leads to additional performance gains of up to 4 dB.

The three-dimensional video (3DV) is composed of variable-length stream sequences captured via diversified cameras surrounding an object. Thus, it is an urgent task to accomplish sufficient encoding to be compatible with incoming bandwidth demands, while achieving a recommended 3DV reception performance. In the 3DV compression framework, the lost macro-blocks (MBs) might propagate into the following frames and the adjoining views. Therefore, it is obligatory to avoid error propagation by concealing the corrupted MBs at the decoder through the utilization of appropriate post-processing error concealment (EC) techniques. The existing EC algorithms fundamentally exploit the temporal, inter-view, and spatial matching within the 3DV frames and views to reconstruct the disparity vectors (DVs) and motion vectors (MVs) of the corrupted MBs. Unluckily, in the state of high severe corruptions and heavily erroneous MBs, these concealment algorithms are predominantly unreliable and might give unreliable 3DV quality. Thence, in this work, we suggest the utilization of the outer block boundary matching algorithm to estimate the MVs and the directional interpolation EC algorithm to estimate the DVs of the erroneous MBs. After that, the Bayesian Kalman filter (BKF) is employed because of its efficiency to filter out the inherent errors in the previously predicted DVs and MVs to accomplish better 3D video performance. Experimental results on standard 3DV sequences demonstrate that the suggested BKF-based EC scheme is more powerful with heavy losses. It subjectively and objectively outperforms the traditional concealment techniques at severely random and bursty packet loss rates (PLRs).

Aiming at the higher bit-rate occupation of motion vector encoding and more time load of full-searching strategies, a multi-resolution motion estimation and compensation algorithm based on adjacent prediction of frame difference was proposed. Differential motion detection was employed to image sequences and proper threshold was adopted to identify the connected region. Then the motion region was extracted to carry out motion estimation and motion compensation on it. The experiment results show that the encoding efficiency of motion vector is promoted, the complexity of motion estimation is reduced and the quality of the reconstruction image at the same bit-rate as Multi-Resolution Motion Estimation (MRME) is improved.

Confident Recovery for Lost Motion Vectors in Video Transmission

Video transmission in error-prone networks suffers bit errors and packet losses that degrade the decoded video quality. In this paper, a video error concealment scheme based on H.264/AVC is proposed to enhance the error robustness using reversible data hiding. At the encoder, motion vectors of macro blocks belonging to the region of interest (ROI) are embedded into the background region within the same frame. The histogram modification technique based on quantized DCT coefficients of coded macro blocks is used to achieve loss less recovery after data extraction. If a macro block in the ROI is found missing at the decoder, the embedded motion vector can be extracted from the corresponding host macro block for the recovery of the missing macro block. This proposed scheme makes a tradeoff between error concealment performance and compression efficiency. Experimental results show the better reconstructed video quality can be achieved compared with the related error concealment methods.

This paper introduces a novel scheme of motion estimation (ME) and motion compensation (MC) in wavelet transform (WT) video coding. The scheme is unique in that half-pixel resolution ME and MC are applied on filtered coefficients ahead of decimation to preserve motion consistency and yet achieve minimal prediction residue. An efficient motion-compensated WT video coding system is built based on the proposed ME and MC. In the coding scheme, according to the property of embedded zerotree wavelet (EZW) coding, the mean square error (MSE) criterion is used in ME instead of normally adopted sum of absolute difference, and an overlapped MC algorithm is developed to combat the block effect introduced by block-based ME and improve peak signal-to-noise ratio (PSNR) performance. The superior performance of the proposed scheme is demonstrated with experimental results.