Perceptual quality assessment for H.264/AVC compression
The paper proposes a No-Reference (NR) metric to objectively assess the H.264/AVC video quality. The proposed model takes into account the typical artefacts introduced by hybrid block-based motion compensated predictive video codecs as the one related to the H.264/AVC standard. More specifically, th...
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creator | Romaniak, P. Janowski, L. Leszczuk, M. Papir, Z. |
description | The paper proposes a No-Reference (NR) metric to objectively assess the H.264/AVC video quality. The proposed model takes into account the typical artefacts introduced by hybrid block-based motion compensated predictive video codecs as the one related to the H.264/AVC standard. More specifically, these artefacts are the blockiness introduced at the boundaries of each coded block and the temporal flickering due to different coding modes used for the same macroblock along the video sequence. Furthermore, a flickering metric for intra coded frames is also derived. The quality prediction accuracy of the proposed NR quality metric is validated over subjective data collected during a video subjective evaluation experiments. Moreover, the quality prediction accuracy is also compared with the one provided by the well known state-of-the-art Structural SIMilarity (SSIM) metric which works in a full-reference mode. The proposed metric achieves a higher Pearson's correlation coefficient with subjective scores than the one achieved by the SSIM metric. |
doi_str_mv | 10.1109/CCNC.2012.6181021 |
format | Conference Proceeding |
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The proposed model takes into account the typical artefacts introduced by hybrid block-based motion compensated predictive video codecs as the one related to the H.264/AVC standard. More specifically, these artefacts are the blockiness introduced at the boundaries of each coded block and the temporal flickering due to different coding modes used for the same macroblock along the video sequence. Furthermore, a flickering metric for intra coded frames is also derived. The quality prediction accuracy of the proposed NR quality metric is validated over subjective data collected during a video subjective evaluation experiments. Moreover, the quality prediction accuracy is also compared with the one provided by the well known state-of-the-art Structural SIMilarity (SSIM) metric which works in a full-reference mode. 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source | IEEE Electronic Library (IEL) Conference Proceedings |
subjects | Correlation Encoding Image coding Mathematical model Measurement Streaming media Training |
title | Perceptual quality assessment for H.264/AVC compression |
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