Improved integral images compression based on multi-view extraction

Antoine Dricot (1, 2) , Joël Jung (2) , Marco Cagnazzo (1, 3, 4) , Béatrice Pesquet , Frédéric Dufaux (1, 5)

1 LTCI - Laboratoire Traitement et Communication de l'Information
2 Orange Labs [Issy les Moulineaux]
3 IDS - Département Images, Données, Signal
4 MM - Multimédia
5 L2S - Laboratoire des signaux et systèmes

Integral imaging is a technology based on plenoptic photography that captures and samples the light-field of a scene through a micro-lens array. It provides views of the scene from several angles and therefore is foreseen as a key technology for future immersive video applications. However, integral images have a large resolution and a structure based on micro-images which is challenging to encode. A compression scheme for integral images based on view extraction has previously been proposed, with average BD-rate gains of 15.7% (up to 31.3%) reported over HEVC when using one single extracted view. As the efficiency of the scheme depends on a tradeoff between the bitrate required to encode the view and the quality of the image reconstructed from the view, it is proposed to increase the number of extracted views. Several configurations are tested with different positions and different number of extracted views. Compression efficiency is increased with average BD-rate gains of 22.2% (up to 31.1%) reported over the HEVC anchor, with a realistic runtime increase.

Mots clés: Integral imaging; plenoptic; multi-view extraction; compression; 3D-HEVC

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

Antoine Dricot, Joël Jung, Marco Cagnazzo, Béatrice Pesquet, Frédéric Dufaux. Improved integral images compression based on multi-view extraction. Applications of Digital Image Processing XXXIX, SPIE, Aug 2016, San Diego, United States. pp.99710L, ⟨10.1117/12.2238707⟩. ⟨hal-01436104⟩