Quality-based improvement of Quantization for Light Field Compression

Raphaël Lerbour (1) , Bruno Mercier (1) , Daniel Meneveaux (1) , Mohamed-Chaker Larabi (1)

1 SIC - SIGNAL-IMAGE-COMMUNICATION

In the last decade, many methods have been proposed for rendering image-based objects. However, the number and the size of the images required are highly memory demanding. Based on the light field data structure, we propose an improved compression scheme favoring visual appearance and fast random access. Our method relies on vector quantization for preserving access in constant time. 2D Bounding boxes and masks are used to reduce the number of vectors during quantization. Several light field images are used instead of blocks of 4D samples, so that image similarities be exploited as much as possible. Psychophysical experiments performed in a room designed according to ITU recommendations validate the quality metrics of our method.

Keywords: Image-based rendering; light field; compression; subjective assessment

Domains: Image Processing [eess.IV]; Graphics [cs.GR]

Raphaël Lerbour, Bruno Mercier, Daniel Meneveaux, Mohamed-Chaker Larabi. Quality-based improvement of Quantization for Light Field Compression. 2nd International Conference on Computer Graphics Theory and Applications, Mar 2007, Barcelona, Spain. pp.235-243. ⟨hal-00337700⟩