An Adaptive Spatio-Temporal Error Concealment Scheme Based on H.264/AVC

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).

A robust error concealment (EC) scheme for transmission of JPEG-coded images over error-pronewireless networks is proposed. It incorporates data-hiding as a correction element along with spatial redundancy of natural images to reconstruct lost portions of a received image signal. To handle burst packet-loss conditions experienced in wireless transmission links, the use of interleaving and interleaved forward error correction is studied. In this context, the trade-off between complexity and quality of error concealment is investigated. We provide simulative evidence that the proposed EC scheme improves over state-of-the-art algorithms known from the literature.

Consecutive corrupted MBs or slice errors are commonly seen in modern video transmission systems. Temporal error concealment is an effective approach to reduce the impact of errors. Conventional temporal error concealment techniques recover slice errors on a MB basis. We propose a new novel temporal scheme for slice error concealment based on a size-adaptive region basis. Size-adaptive region boundary matching can significantly reduce the misalignments or side mismatches that are commonly seen in MB-based approaches. Instead of using MSE or MAE as the matching criteria, We propose a matching criterion based on structural similarity (SSIM). Our proposed matching criterion can achieve better structural alignments and better visual perceptual quality. We also propose a method to detect motion vector outliers at the last stage of the error concealment scheme, which can further improve the visual quality of the concealed videos. Our proposed scheme conceals slice errors with good accuracy as well as low computation complexity, and it can be applied for real-time applications.

The performance of MPEG video transmission over error-prone channels is limited by the channel noise. An efficient error concealment (EC) scheme is essential for diminishing the impact of transmission errors in a compressed video, A number of EC techniques have been developed to combat the transmission errors. However, the previous techniques are always inefficient when the motions of video object are fast or complex. This paper proposes a novel adaptive EC algorithm to conceal the error for block and motion-compensation based video coding systems. The proposed EC method employs an unsupervised artificial neural network (ANN) model, i.e. self-organizing map (SOM), as a predictor to estimate the motion vectors of the damaged macroblocks (MBs). Then the estimated motion vectors were utilized to reconstruct the damaged MB by exploiting the spatial information from reference frames based on the boundary matching criterion. Because of the SOM has a great capacity for visualizing and interpreting high-dimensional data sets, the estimation model proposed herein can exploit the nonlinearity property of the SOM to estimate lost motion vectors more accurately. Computer simulations show that the visual quality and the PSNR evaluation of reconstructed frames are significantly improved by using the proposed EC algorithm. Thus, the proposed algorithm is expected to be practical for motion vector compressed video in error-prone networks.

Purpose – The purpose of this paper is to solve the pack loss problem of video transmitted over error‐prone channels. Pack loss generally affects the visual quality of reconstructed frames significantly. Consequently, a grey approach to error concealment (EC) is proposed.Design/methodology/approach – Note that missing information in error blocks can be found before and after the error frame. Thus, two adjacent error‐free frames are utilized to conceal error blocks caused by packet loss. This paper presents an EC approach based on grey polynomial interpolation (GPI) which is called the GTEC. In the GTEC, the following stages are involved. First, error blocks due to packed loss are detected. Then, optimal reference blocks in adjacent frames are found through boundary matching algorithm (BMA). Finally, estimated blocks are obtained by the GPI. By replacing error blocks with the estimated blocks, EC is completed in the GTEC.Findings – In the simulation, the proposed GTEC is compared with the EC scheme in H.26...

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.

In this paper, a prescription-based error concealment (PEC) method is proposed. PEC relies on pre-analyses of the concealment error image (CEI) for I-frames and the optimal error concealment scheme for P-frames at encoder side. CEI is used to enhance the image quality at decoder side after error concealment (by spatial interpolation or zero motion) of the corrupted intra-coded MBs. A set of pre-selected error concealment methods is evaluated for each corrupted inter-coded MB to determine the optimal one for the decoder. Both the CEI and the scheme indices are considered as the prescriptions for decoder and transmitted along with the video bit stream based on a reversible data embedding technique. Experiments show that the proposed method is capable of achieving PSNR improvement of up to 1.48 dB, at a considerable bit-rate, when the packet loss rate is 20%

Distributed Video Coding (DVC) is based on a new paradigm in coding, which has received many interests recently. Among other features, DVC is said to provide better error resiliency. This paper proposes a hybrid spatial and temporal error concealment scheme to conceal errors in Wyner-Ziv (WZ) frames. We first use a spatial concealment based on edge directed filter. This step is exploited to improve the performance of subsequent temporal concealment. An enhanced temporal concealment based on motion compensated temporal interpolation is proposed, including motion vector refinement and smoothing, optimal compensation mode selection, and a new matching criterion for motion estimation. Simulation results show that the objective qualities as well as the perceptual qualities of the corrupted sequences are significantly improved by the hybrid error concealment, outperforming both spatial and temporal concealments alone.

In this paper, we propose a joint temporal error control (JTEC) method for H.264 which combines RDO-based macroblock (MB) classification at the encoder and adaptive partition size error concealment at the decoder. The encoder classifies the MBs by evaluating the sensitivity of the MBs as the RD cost between the concealment error and the bits needed for the additional motion information. Additional motion information can be transmitted for the error sensitive MBs such as the original motion vector or motion vector index. The decoder utilizes the additional motion information for the sensitive blocks. Non-sensitive blocks are concealed by the Adaptive Partition Size (APS) method. APS selects the best partition mode for error concealment by minimizing the Weighted Double-Side External Boundary Matching Error (WDS-EBME), which jointly measures the inter-MB boundary discontinuity, inter-partition boundary discontinuity and intra-partition block artifacts in the recovered MB. A progressive concealment method is developed for the 4x4 partition mode.

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.

Error concealment at a decoder is an efficient method to reduce the degradation of visual quality caused by channel errors. In this paper, we propose a novel spatio-temporal error concealment algorithm based on the spatial-temporal fading (STF) scheme which has been recently introduced. Although STF achieves good performance for the error concealment, several drawbacks including blurring still remain in the concealed blocks. To alleviate these drawbacks, in the proposed method, hybrid approaches with adaptive weights are proposed. First, the boundary matching algorithm and the decoder motion vector estimation which are well-known temporal error concealment methods are adaptively combined to compensate for the defect of each other. Then, an edge preserved method is utilized to reduce the blurring effects caused by the bilinear interpolation for spatial error concealment. Finally, two concealed results obtained by the hybrid spatial and temporal error concealment are pixel-wisely blended with adaptive weights. Experimental results exhibit that the proposed method outperforms conventional methods including STF in terms of the PSNR performance as well as subjective visual quality, and the computational complexity of the proposed method is similar to that of STF.

In this paper a hybrid error concealment algorithm using linear interpolation is proposed. In the proposed hybrid algorithm, the selective motion field interpolation (SMFI) is employed to conceal the erroneous macroblock. The spatial and temporal boundary-matched errors are then used to check whether the SMFI conceals the erroneous macroblock properly. If the temporally recovered macroblock is reconstructed incorrectly, the spatial error concealment using linear interpolation is employed to conceal the damaged macroblock instead of SMFI.It can achieve better performance subjectively as well as objectively over other error concealment techniques such as AMV, FBBM and MFI. Simulation was conducted on the H.263 codec and the experimental results reveal that the proposed algorithm significantly outperforms other concealment techniques.

We introduce model-based schemes for error concealment of networked video. We build appearance models for specific objects in the scene and use these models to replenish any lost information. Due to the models being designed specifically for the object, they are able to capture the statistical variations in the object appearance more effectively, thereby leading to better error-concealment performance. We examine statistical modeling techniques from the literature and introduce a new efficient and accurate linear model for data representation, called the mixture of principal components (MPC), and use these models for error concealment. We simulate lossy network conditions and show that these model-based concealment schemes outperform traditional concealment schemes across a variety of loss probabilities and bit rates for the coded video.

Image coding algorithms such as Vector Quantisation (VQ), JPEG and MPEG have been widely used for encoding image and video, These compression systems utilise block-based coding techniques to achieve a higher compression ratio. However, a cell loss or a random bit error during network transmission will permeate into the whole block, and then generate several damaged blocks. Therefore, an efficient Error Concealment (EC) scheme is essential for diminishing the impact of damaged blocks in a compressed image. In this paper, a novel adaptive EC algorithm is proposed to conceal the error for block-based image coding systems by using neural network techniques in the spatial domain. In the proposed algorithm, only the intra-frame information is used for reconstructing the image with damaged blocks. The information of pixels surrounding a damaged block is used to recover the errors using the neural network models. Computer simulation results show that the visual quality and the PSNR evaluation of a reconstructed image are significantly improved using the proposed EC algorithm.

We propose an error concealment scheme for MPEG-2 compressed (AAC) audio using a novel modulo watermarking technique. It can be used on top of other error control schemes. After the modulo watermark is embedded, MPEG-2 AAC audio only shows negligible file size increase and moderate SNR penalty. For audio transmission over packet-switch networks (e.g., the Internet), using our watermark-based concealment scheme shows consistent SNR gain over using conventional concealment schemes.