Grey temporal error concealment

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.

An Adaptive Spatio-Temporal Error Concealment (ASTEC) scheme based on H.264/AVC is proposed in the paper to improve the quality of the rebuilt frame in H.264/AVC decoder side. Combining the spatial error concealment method with the temporal one, a new scheme is proposed to conceal an erroneous macro block according to its encoded mode. The temporal error concealment scheme adopts the weighted Boundary Matching Algorithm to recover the erroneous macro block. The spatial error concealment scheme recovers the erroneous macro block by exploiting the directional interpolation which subdivides the macro block according to the number and the direction of edges going through it. Experiments show that the proposed concealment scheme can restrain the diffusion of erroneous macro block and improve the quality of the rebuilt frame subjectively as well as objectively.

Video transmission over wireless networks becomes a major part of multimedia studies especially after fourth-generation communication standard has been introduced. There is a growing need to improve video visual quality, while its computational complexity should remain low. One of the low-complexity Error Concealment (EC) methods for missing macroblock (MB) recovery is Boundary Matching Algorithm (BMA). Nevertheless, this method suffers from lack of accuracy. In this paper, we propose a novel modified BMA method by exploiting the correlation of the pixels on the edge of the missing MB. The performance of this method is explained in detail and extra experimental results are given to demonstrate its superiority over BMA method.

We use particle filtering for correcting the erroneous motion vectors (MVs), which are derived from the boundary matching algorithm (BMA) in packet video communications. Assuming a two-state Markov channel model for transmission, the error of the extracted MVs by BMA is shown to be modeled by the Gaussian mixture distribution. Formulating the problem in the state space, we deploy particle filtering for denoising the erroneous MVs. The main challenge of using particle filters is high computational complexity that is directly related to the number of particles. The proposed particle filtering scheme is efficient even if the number of particles is decreased. Experimental results are provided to show the efficiency of this filtering approach compared to a recent scheme based on Kalman filtering. The experiments show meaningful increase in the quality of the recovered video sequences in terms of PSNR up to 3 dB compared with the other error concealment techniques. Also, the computational complexity of the proposed scheme is discussed.

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.

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.

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.

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.

In video coding, error concealment is one of the techniques integrated to ensure the error-resilience of a video sequence. As of the current HM Reference Software [5], only frame-level error concealment can be performed by the codec. In this study, the author evaluates the performance of a slice-level error concealment scheme. The experimental setup consists of three video sequences with varying levels of motion activity: low, medium, and high. Each sequence is subject to five Packet Error Rates (PER) with five trials each and with a bitrate of 32kbps and 128 kbps. Afterwards, the PSNR for each frame is calculated. The frame PSNRs would then be used to calculate the average PSNR for each sequence. To generate the error patterns, a simulation of a wireless channel is created using Network Simulator (NS2). The simulation was modeled using Rayleigh fading and two-state Markov error model. The information resulting from this is used to allow the decoder to determine which slices are set for concealment. Based on the results, it can be seen that sequences with low motion activity benefit the most from error concealment while those with high motion activity fail to maintain the same quality.

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%

Low-complexity error concealment techniques for mobile applications are studied extensively in this paper. The boundary matching algorithm (BMA) is an attractive choice for mobile video concealment due to its low complexity. Here, we examine a variant of BMA called the outer boundary matching algorithm (OBMA). Although BMA and OBMA are similar in their design principle, it is empirically observed that OBMA outperforms BMA by a significant margin (typically, 0.5 dB or higher) while maintaining the same level of complexity. In this work, we attempt to explain the superior performance of OBMA, and conclude that OBMA provides an excellent tradeoff between the complexity and the quality of concealed video for a wide range of test video sequences and error conditions.

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.

This paper presents an evaluation of the latest MPEG-5 Part 2 Low Complexity Enhancement Video Coding (LCEVC) for video streaming applications using best effort protocols. LCEVC is a new video standard by MPEG, which enhances any base codec through an additional low bitrate stream, improving both video compression efficiency and and transmission. However, there is an interplay between packetization, packet loss visibility, choice of codec and video quality, which implies that prior studies with other codecs may be not as relevant. The contributions of this paper is, therefore in twofold: It evaluates the compression performance of LCEVC and then the impact of packet loss on its video quality when compared to H.264 and HEVC.The results from this evaluation suggest that, regarding compression, LCEVC outperformed its base codecs, overall in terms average encoding bitrate savings when using the constant rate factor (CRF) rate control. For example at a CRF of 19, the average encoding bitrate was reduced by 18.7% and 15.8% when compared with the base H.264 and HEVC codecs respectively. Furthermore, LCEVC produced better visual quality across the packet loss range compared to its base codecs and the quality only started to decrease once packet loss exceeded 0.8-1%, and decreases at a slower pace compared to its equivalent base codecs. This suggests that the LCEVC enhancement layer also provides error concealment. The results presented in this paper will be of interest to those considering the LCEVC standard and expected video quality in error-prone environments

Error concealment at the decoder side is an economical approach to ensuring an acceptable and stable video quality in case of packet erasure or loss, and thus attracts lots of interest. Current techniques mainly employ the spatial or temporal correlation to predict the motion vectors of the missing blocks, and interpolation, extrapolation or boundary matching schemes are usually effective. However, for heavily corrupted sequences, e.g., with macroblock loss rate beyond 50%, most methods might perform less satisfactorily. Inspired by the tracking efficiency of Kalman filter, in the present work, we adopted it to predict the missing MVs, and the unpredicted ones (minority) were recovered complementarily by using the bilinear motion field interpolation (MFI) method. The experimental results on typical sequences reveal that the proposed algorithm outperforms the boundary matching algorithm and the MFI technique by up to about 4.77 dB and 3.66 dB respectively for heavily corrupted videos.

Compressed video streams are very exposed to channel losses when they are transmitted through an unreliable network. The predictive encoding scheme is efficient but even a single packet loss can cause decoding error propagation through all the frames following the erasure. An error-resilience approach to tackle this problem is the multiple description coding (MDC) technique. Another important issue connected to this approach is the problem of the error-concealment (EC) used to reconstruct the information lost during the transmission. In this paper, we deal with a sequence-based EC algorithm that performs the error-concealment by using the information coming from a certain number of frames in the future to minimize the effect of error propagation. The target of this work is applying such an EC strategy to a balanced MDC system. Simulation results show the great improvement that a sequence-based EC algorithm can give compared to classical EC approaches.