The challenges encountered when converting formats are addressed in the papers ’Optimizing UHD Production With Super Resolution Techniques’ by Xavier Ducloux, ’Using a Colour Appearance Model accounting for the human visual system for down-mapping Hybrid Log-Gamma (HLG) to Standard Dynamic Range (SDR)’ by Daniel-Dee Lofthouse-Smith and in the paper ’CNN based correction of quantization artifacts for SDR to HDR conversions’.

Whilst the enhanced video formats of Ultra High Definition (UHD), Wide Colour Gamut (WCG) and High Dynamic Range (HDR) present in spectacular quality – they also bring a myriad of format conversion challenges, whether that is up-converting legacy content for use in new productions or down-converting HDR/WCG to suit traditional devices.

IBC Digital Watch presentations on ’Optimizing UHD Production With Super Resolution Techniques’ by Xavier Ducloux, ’Using a Colour Appearance Model accounting for the human visual system for down-mapping Hybrid Log-Gamma (HLG) to Standard Dynamic Range (SDR)’ by Daniel-Dee Lofthouse-Smith 

In this session, we address both of these challenges – one demonstrating an effective colour mapping model that takes into account the behaviour of the human visual system and the other using machine-learning for super-resolution in a production environment. Our supporting paper continues the enhancement theme assessing the effectiveness of machine learning to reduce coding artefacts.

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