Color correction algorithm based on camera characteristics for multi-view video coding

Various types of multi-view camera systems have been proposed for capturing three dimensional scenes. Yet, color distributions among multi-view images remain inconsistent in most cases, degrading multi-view video coding performance. In this paper, we propose a color correction algorithm based on the camera characteristics to effectively solve such a problem. Initially, we model camera characteristics and estimate their coefficients by means of correspondences between views. To consider occlusion in multi-view images, correspondences are extracted via feature-based matching. During coefficient estimation with nonlinear regression, we remove outliers in the extracted correspondences. Consecutively, we generate lookup tables for each camera using the model and estimated coefficients. Such tables are employed for fast color converting in the final color correction process. The experimental results show that our algorithm enhances coding efficiency with gains of up to 0.9 and 0.8 dB for luminance and chrominance components, respectively. Further, the method also improves subjective viewing quality and reduces color distance between views.