No-reference quality assessment of DIBR-synthesized videos by measuring temporal flickering

Zhou, Yu; Li, Leida; Wang, Shiqi; Wu, Jinjian; Zhang, Yun

doi:10.1016/j.jvcir.2018.05.023

Cited by 15 publications

(5 citation statements)

References 31 publications

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“…Generally, a better metric produces higher PLCC and SRCC values, as well as a lower RMSE value. To validate the advantages of the proposed metric, five DIBR‐synthesised VQA metrics are employed for comparison, including CQM [10 ], PSPTNR [12 ], CTI [9 ], NR_MWT [13 ] and FDI [11 ]. Furthermore, six representative DIBR‐synthesised IQA metrics are also compared, including Bosc [3 ], 3DSwIM [4 ], MW‐PSNR [5 ], MP‐PSNR [6 ], NIQSV+ [7 ] and APT [8 ].…”

Section: Resultsmentioning

confidence: 99%

“…For DIBR‐synthesised videos, temporal distortions such as local flickering will destroy the spatiotemporal consistency, which heavily degrades the QoE of end users [11 ]. To measure the temporal distortions, we further propose an energy‐based sequence mapping strategy to calculate the bi‐order similarities between synthesised and reference videos.…”

Section: Proposed Metricmentioning

confidence: 99%

“…Finally, the critical temporal inconsistency (CTI) metric was proposed by pooling the quality scores of all synthesised frames. In [11 ], the flickering distortion intensity (FDI) metric was proposed. The temporal gradient variation was applied to detect the flickering regions, based on which the distortion intensity was quantified in the singular value decomposition (SVD) domain.…”

Section: Introductionmentioning

confidence: 99%

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DIBR‐synthesised video quality assessment by measuring geometric distortion and spatiotemporal inconsistency

Huang

Zhou

et al. 2020

Electron. lett.

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Depth‐image‐based rendering (DIBR), as the most popular view synthesis method, is commonly used in the application of multi‐view and free‐viewpoint videos. However, the quality evaluation of DIBR‐synthesised videos remains largely unexplored, which may hinder the development of more advanced view synthesis technology. With this motivation, this Letter presents a new quality metric for DIBR‐synthesised videos. Specifically, the disoccluded regions are first detected based on an adaptive threshold to quantify geometric distortions. An energy‐based sequence mapping strategy is proposed to portray spatiotemporal inconsistency by calculating first‐order and second‐order similarities in the gradient magnitude domain and the Laplace‐of‐Gaussian domain, respectively. Finally, the overall quality score is generated by pooling the scores of geometric distortion and spatiotemporal inconsistency. Experimental results demonstrate that the proposed metric outperforms the state‐of‐the‐art metrics dedicated to DIBR‐synthesised images and videos.

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Section: Resultsmentioning

confidence: 99%

Section: Proposed Metricmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

DIBR‐synthesised video quality assessment by measuring geometric distortion and spatiotemporal inconsistency

Huang

Zhou

et al. 2020

Electron. lett.

Self Cite

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“…In [67], Zhou et al proposed a NR metric FDI to measure the temporal flickering distortion in the DIBR-synthesized videos. Firstly, the gradient variations between each frame are used to extract the potential flickering regions.…”

Section: Nr Metricsmentioning

confidence: 99%

Quality assessment of DIBR-synthesized views: An overview

et al. 2021

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“…Farid et al [32] designed an NR synthesised IQA method by considering the influence of side‐views information and the distortion of the depth map. Zhou et al [33] proposed a synthesised IQA method for the flicker distortion by calculating the gradient distance between two adjacent frames. Tian et al [34] proposed an NR synthesised IQA method, which mainly considered three kinds of distortion regions.…”

Section: Related Workmentioning

confidence: 99%

Blind quality assessment for 3D synthesised video with binocular asymmetric distortion

et al. 2020

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During the process of watching 3D synthesised video (3D‐SV) and switching viewpoints, there is a case of asymmetric distortion, the left(right) viewpoint is a synthesised video generated by rendering technique, and the right(left) viewpoint is a real video taken by the camera. How to accurately estimate the quality of 3D‐SV with binocular asymmetric distortions is a new and challenging problem. Aiming at this problem, a blind quality assessment method for 3D‐SV with binocular asymmetric distortions is proposed. Firstly, the local edge deformations of synthesised videos at different scales are measured by calculating their standard deviations. Secondly, the global naturalness of synthesised videos is computed by analysing their natural statistical characteristics. Thirdly, a strategy for fusing left and right quality scores is proposed, which considers their texture information in different directions. Finally, the random forest is used to obtain an objective quality score. The experimental results show the superiority of the proposed method on asymmetry 3D‐SV database.

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No-reference quality assessment of DIBR-synthesized videos by measuring temporal flickering

Cited by 15 publications

References 31 publications

DIBR‐synthesised video quality assessment by measuring geometric distortion and spatiotemporal inconsistency

DIBR‐synthesised video quality assessment by measuring geometric distortion and spatiotemporal inconsistency

Quality assessment of DIBR-synthesized views: An overview

Blind quality assessment for 3D synthesised video with binocular asymmetric distortion

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