Coding and cell-loss recovery in DCT-based packet video

Zhu, Qin-Fan; Wang, Y.; Shaw, L.

doi:10.1109/76.224235

Cited by 155 publications

(92 citation statements)

References 16 publications

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“…Therefore, MB edge smoothness has been extensively employed as a minimization criterion to choose the best concealment, when multiple options are available in [102]. Later on, work in [103] extended this technique to include temporal smoothness as a criterion. Table 4 is a summary of the advantages and disadvantages of each error concealment type.…”

Section: Optimization Criteriamentioning

confidence: 99%

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Innovations in Video Error Resilience and Concealment

Fleury¹,

Moiron²,

Ghanbari³

2011

RPTSP

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Router buffer overflow and random bit errors have always been a problem in the Internet. The growth in multimedia applications in mobile extensions of the Internet has increased the threat from error bursts, random errors, and packet erasures that are a manifestation of wireless channels. Source-coded error resilience has come to prominence in the H.264/AVC codec standard, and this paper reviews such innovations surrounding this codec. Some innovations are new variants of an existing technique such as datapartitioning and some are entirely new such as the powerful dispersed-mode flexible macroblock ordering. Other techniques, such as reversible variable length coding, were not be transferred to H.264 from earlier codecs and, hence, innovations are proposed to still provide robust entropy coding. Other variants such as adaptive intra-refresh are still being experimented with. When error resilience or other protection methods fail to present an adequate video frame then error concealment can be brought to bear. This paper reviews error concealment which is important to commercial companies as they are able to distinguish their codec from others. The paper considers spatial, temporal and hybrid error concealment methods. Though this paper contains over one hundred references it can only provide a slice through this rich field.

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Section: Optimization Criteriamentioning

confidence: 99%

“…In error concealment, the same concept applies and consequently hybrid spatio-temporal error concealment [96][97] [98][99] can be applied. Techniques which use information from the current frame as well as from previous decoded frames can typically perform better.…”

Section: Spatio-temporal Error Concealmentmentioning

confidence: 99%

Innovations in Video Error Resilience and Concealment

Fleury¹,

Moiron²,

Ghanbari³

2011

RPTSP

View full text Add to dashboard Cite

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“…Since packet loss can result in the loss of entire rows of macroblocks in an image, packetization techniques that rely on interleaving data have been proposed in [17,23,24,25].…”

Section: Previous Workmentioning

confidence: 99%

“…Missing macroblocks can be reconstructed by estimating their low frequency DCT coefficients from the DCT coefficients of the neighboring macroblocks [24,30,31,32], by estimating missing edges in each block from edges in the surrounding blocks as proposed in [34], or by the method of projections onto convex sets [40] as described in [35].…”

Section: Previous Workmentioning

confidence: 99%

“…Post processing (passive) techniques for the sake of error concealment utilize spatial data, or temporal data, or a hybrid of both [5,24,[26][27][28][29][30][31][32][33][34][35][36][37][38][39]. Missing macroblocks can be reconstructed by estimating their low frequency DCT coefficients from the DCT coefficients of the neighboring macroblocks [24,30,31,32], by estimating missing edges in each block from edges in the surrounding blocks as proposed in [34], or by the method of projections onto convex sets [40] as described in [35].…”

Section: Previous Workmentioning

confidence: 99%

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Error Concealment in Encoded Video Streams

Salama

Shroff

Delp

1998

Signal Recovery Techniques for Image and Video Compression and Transmission

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When transmitting compressed video over a data network, one has to deal with how channel errors affect the decoding process. This is particularly problematic with data loss or erasures. In this paper we describe techniques to address this problem in the context of networks where channel errors or congestion can result in the loss of entire macroblocks when MPEG video is transmitted. We describe spatial and temporal techniques for the recovery of lost macroblocks. In particular, we develop estimation techniques for the reconstruction of missing macroblocks using a Markov Random Field model. We show that the widely used heuristic motion compensated error concealment technique based on averaging motion vectors is a special case of our estimation technique. We further describe a technique that can be implemented in real-time.

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