Objective measurement of transcoded video quality in mobile applications

Palaniappan, Ramanathan; Suresh, Nitin; Jayant, N.

doi:10.1109/wowmom.2008.4594912

Cited by 2 publications

(2 citation statements)

References 2 publications

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“…The former are detected using a combination of the quantization step size and scene activity whereas the latter are detected during error concealment. Therefore, the AVQ metric requires access to both the network bitstream and the decoded video sequence [34].…”

Section: Visual Quality Impairment Detectionmentioning

confidence: 99%

No-Reference Bitstream-Based Visual Quality Impairment Detection for High Definition H.264/AVC Encoded Video Sequences

Staelens

Wallendael

Crombecq

et al. 2012

IEEE Trans. on Broadcast.

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Abstract-Ensuring and maintaining adequate Quality of Experience towards end-users are key objectives for video service providers, not only for increasing customer satisfaction but also as service differentiator. However, in the case of High Definition video streaming over IP-based networks, network impairments such as packet loss can severely degrade the perceived visual quality. Several standard organizations have established a minimum set of performance objectives which should be achieved for obtaining satisfactory quality. Therefore, video service providers should continuously monitor the network and the quality of the received video streams in order to detect visual degradations. Objective video quality metrics enable automatic measurement of perceived quality. Unfortunately, the most reliable metrics require access to both the original and the received video streams which makes them inappropriate for real-time monitoring. In this article, we present a novel no-reference bitstream-based visual quality impairment detector which enables real-time detection of visual degradations caused by network impairments. By only incorporating information extracted from the encoded bitstream, network impairments are classified as visible or invisible to the end-user. Our results show that impairment visibility can be classified with a high accuracy which enables real-time validation of the existing performance objectives.

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Section: Visual Quality Impairment Detectionmentioning

confidence: 99%

No-Reference Bitstream-Based Visual Quality Impairment Detection for High Definition H.264/AVC Encoded Video Sequences

Staelens

Wallendael

Crombecq

et al. 2012

IEEE Trans. on Broadcast.

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“…In 2D videos, video quality is either measured using objective metrics such as mean square error or subjective metrics such as mean opinion score and mean time between failures [2]. However, measuring 3D video quality poses additional challenges due to the third dimension of depth that is perceived by the human brain.…”

Section: Introductionmentioning

confidence: 99%

Visual quality in stereoscopic 3DTV

Palaniappan

Jayant

Mane³

2012

2012 Conference Record of the Forty Sixth Asilomar Conference on Signals, Systems and Computers (ASILOMAR)

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Georgia Tech has an ongoing research program in multimedia communications, including visual quality assessment in 3DTV. As part of our 3D related research, we have studied the response of the human visual system to compressed 3D sequences and compared the visibility of artifacts in 3D and 2D views (individual left-eye and right-eye views) over a broad range of bitrates. Using mean opinion score (MOS) as the metric, we have conducted subjective tests as well as HVS-tuned objective measurements needed to perform the 2D vs 3D comparison. Our initial results show that there exists a bitrate threshold above which compression artifacts tend to get suppressed in the 3D view when compared to the 2D view. Our tests also show that this artifact suppression threshold is content dependent.

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Objective measurement of transcoded video quality in mobile applications

Cited by 2 publications

References 2 publications

No-Reference Bitstream-Based Visual Quality Impairment Detection for High Definition H.264/AVC Encoded Video Sequences

No-Reference Bitstream-Based Visual Quality Impairment Detection for High Definition H.264/AVC Encoded Video Sequences

Visual quality in stereoscopic 3DTV

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