Improved integral images compression based on multi-view extraction

Antoine Dricot; Joel Jung; Marco Cagnazzo; Béatrice Pesquet; Frédéric Dufaux

doi:10.1117/12.2238707

27 September 2016 Improved integral images compression based on multi-view extraction

Antoine Dricot, Joel Jung, Marco Cagnazzo, Béatrice Pesquet, Frédéric Dufaux

Proceedings Volume 9971, Applications of Digital Image Processing XXXIX; 99710L (2016) https://doi.org/10.1117/12.2238707
Event: SPIE Optical Engineering + Applications, 2016, San Diego, California, United States

Abstract

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.

Conference Presentation

Citation Download Citation

Antoine Dricot, Joel Jung, Marco Cagnazzo, Béatrice Pesquet, and Frédéric Dufaux "Improved integral images compression based on multi-view extraction", Proc. SPIE 9971, Applications of Digital Image Processing XXXIX, 99710L (27 September 2016); https://doi.org/10.1117/12.2238707

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