A Maximum Likelihood Approach to Video Error Correction Applied to H.264 Decoding

IEEE Trans. Circuits Syst. Video Technol.

2015

Self Cite

Abstract-Error concealment has long been identified as the last line of defense against transmission errors. Since error handling is outside the scope of video coding standards, decoders may choose to simply ignore corrupted packets or attempt to decode their content. In this paper, we present a novel joint source-channel decoding approach that can be applied to received video packets containing transmission errors. Soft-output information is combined with our novel syntax-element-level maximum likelihood decoding framework to effectively extract valid macroblocks from corrupted H.264 slices. Simulation results show that our video error correction strategy provides an average PSNR improvement neer 2 dB compared to the error concealment approach used by the H.264 reference software, as well as an average PSNR improvement of 0.8 dB compared to state-of-theart error concealment. The proposed method is also applicable when only hard-information is available, in which case it performs better than state-of-the-art error concealment especially in high error conditions. Finally, in our simulations, the proposed method increased the decoder computational complexity by only 5% to 20%, making it applicable for real-time applications.

Section: Modeling Syntax Elementsmentioning

confidence: 99%

“…Joint source-channel decoding (JSCD) approaches [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33], [34], [35] have also shown that involving the video decoder in the correction process yields better correction capabilities.…”

Section: Introductionmentioning

confidence: 99%

Video Error Correction Using Soft-Output and Hard-Output Maximum Likelihood Decoding Applied to an H.264 Baseline Profile

Caron¹,

IEEE Trans. Circuits Syst. Video Technol.

2015

Self Cite

“…One was to consider this probability as independent Bernoulli trials since the decoder can assume that each bit has the same probability of being in error. The Hamming distance, the number of flipped bits, between the hypothetically transmitted SE (s i,T ) and the received SE (s i,R ) represents the number of successes [33]. The second method involves evaluating the P(s i,R |s i,T ) likelihood function using the soft-output information provided by the channel decoder [34,35].…”

Section: Maximum Likelihood Error Correction Decodingmentioning

confidence: 99%

“…These issues restrict the use of the approaches in low-delay applications. Recently, a less complex approach than list decoding has been proposed in [33][34][35], in which a maximum likelihood decoding (MLD) method is applied at the syntax element (SE) level instead of the whole packet or slice level. The solution space is therefore limited to a set of valid codewords for each specific SE.…”

Section: Introductionmentioning

confidence: 99%

Performance evaluation of maximum likelihood decoding combined with error resilient video coding

Golaghazadeh

2014 IEEE Symposium on Industrial Electronics &Amp; Applications (ISIEA)

Labeau

et al. 2014

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Abstract-In this work, we study the performance of the maximum likelihood decoding (MLD) approach in error-resilient video sequences to establish the performance improvement of this method compared to well-known error concealment approaches. In particular, we consider various interactions between error resilience coding and error concealment/correction. The error resilience methods under consideration include random intra macroblock updating and weighted error resilience. For error concealment/correction, we consider (i) the frame copy (FC), (ii) spatio-temporal boundary matching error concealments (STBMA), and (iii) MLD error correction. Our experimental results show that the best performance is achieved when the MLD interacts with weighted error resilience. Together, they yield, on average, about a 2 dB gain over using FC error concealment with weighted error resilience and a 1 dB gain over STBMA with identical error resilience. Furthermore, MLD with error resilience can be more than 10 dB better than FC without error resilience in certain cases.

“…In our previous work [9], we showed that slices can be viewed as a sequence of transmitted codewordsĉ i , such that S = {ĉ 0 ,ĉ 1 ,ĉ 2 , . .…”

Section: Maximum Likelihood Syntax-element-level Error Correctionmentioning

confidence: 99%

A maximum likelihood approach to correcting transmission errors for joint source-channel decoding of H.264 coded video

Caron

2013 IEEE International Conference on Image Processing

2013

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Real time video applications need to handle transmission errors, as retransmissions are impractical. In this paper, we present a novel joint source channel decoding approach for video error correction. Soft-output information is combined with our syntax element-level maximum likelihood framework to effectively extract valid macroblocks from corrupted H.264 slices. Simulation results show that our video error correction strategy provides better visual quality by reducing the size of the concealment region. Our observations indicate an average PSNR improvement of 0.8 dB (QP=36), with peaks above 10 dB, over state-of-the-art error concealment at a bit error rate of 10 −3 .