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Evaluating the Performance of Existing Full-Reference Quality Metrics on High Dynamic Range (HDR) Video Content

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arxiv 1803.04815 v1 pith:HQEDDXHU submitted 2018-03-13 eess.IV

classification eess.IV
keywords videoqualitymetricscontentdynamicrangeapplicationsdataset
verification ladder T0 review T1 audit T2 compute T3 formal
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While there exists a wide variety of Low Dynamic Range (LDR) quality metrics, only a limited number of metrics are designed specifically for the High Dynamic Range (HDR) content. With the introduction of HDR video compression standardization effort by international standardization bodies, the need for an efficient video quality metric for HDR applications has become more pronounced. The objective of this study is to compare the performance of the existing full-reference LDR and HDR video quality metrics on HDR content and identify the most effective one for HDR applications. To this end, a new HDR video dataset is created, which consists of representative indoor and outdoor video sequences with different brightness, motion levels and different representing types of distortions. The quality of each distorted video in this dataset is evaluated both subjectively and objectively. The correlation between the subjective and objective results confirm that VIF quality metric outperforms all to ther tested metrics in the presence of the tested types of distortions.

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  1. HDRSDR-VQA: A Subjective Video Quality Dataset for HDR and SDR Comparative Evaluation

    cs.CV 2025-05 conditional novelty 6.0 of 10

    A new 960-video subjective quality dataset uses pairwise comparisons to assign JOD scores to HDR and SDR versions of the same content across six TVs.

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