Video enhancement with convex optimization methods

Benoit Boyadjis (1, 2) , Andrei Purica (3) , Béatrice Pesquet-Popescu (3) , Frédéric Dufaux (4)

1 THALES COMMUNICATIONS & SECURITY
2 LTCI - Laboratoire Traitement et Communication de l'Information
3 LTCI - Laboratoire Traitement et Communication de l'Information
4 L2S - Laboratoire des signaux et systèmes

Video enhancement methods enable to optimize the viewing of video content at the end-user side. Most approaches do not consider the compressed nature of the available content. In the present work, we build upon a recently proposed video enhancement approach that explicitly models a compression stage. To apply the enhancement framework on compressed representations requires to extract specific syntax elements during their decoding. This additional information embeds the enhanced result in a domain that closely fits the observation. We evaluate the framework performance in a single source resolution enhancement scenario, and show the method efficiency with respect to state-of-the-art approaches.

Mots clés: video enhancement; super resolution; HEVC; convex optimization

Domaines: Traitement des images [eess.IV]; Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

Benoit Boyadjis, Andrei Purica, Béatrice Pesquet-Popescu, Frédéric Dufaux. Video enhancement with convex optimization methods. IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2018), Apr 2018, Calgary, Canada. ⟨10.1109/icassp.2018.8462357⟩. ⟨hal-01698173⟩