Illumination compensation via low rank matrix completion for multiview video coding

A multi-view video system would capture the same scene from different viewpoints, and suffer from significant illumination variations due to inaccurate camera calibration and varying light conditions. It deteriorates the inter-view correlations and the quality of synthesized views at decoder side. By converting the problem of illumination compensation to noise removing, this paper proposes a low-rank matrix completion algorithm to reduce the effect of illumination variation. Diverged from the existing work which chooses a central view as reference and keeps views consistent, it is dedicated to compensating all the views to match the low-rank structure of views. The discrepancies among views are regarded as mixed noise, and constructed as an incomplete matrix with low-rank. It is solved by a stable matrix completion and obtains a mapping function for color correction. It is robust to outliers since only plausible corresponding points are involved with completion. Experimental results show that the proposed algorithm can increase coding efficiency by up to 0.7 dB for luminance component and up to 2.1 dB for chrominance components.