Color correction of multiview video with average color as reference
When capturing multiview video, there can be significant variations in the color of views captured with different cameras. This negatively affects compression efficiency when multiview video is coded using inter-view prediction. In this paper we propose a method for correcting the color of multiview video sets as a preprocessing step to compression. Unlike previous work where one of the captured views is used as the color reference, we correct all views to match the average color of the set of views. Block based disparity estimation is used to find matching points between all views in the video set, and the average color is calculated for these matching points. Least squares regressions are used to find functions that will make each view match the average color. Experimental results show that the proposed method results in video sets that closely match in subjective color. Furthermore, when multiview video is compressed with JMVM, the proposed method increases compression efficiency by up to 1.0 dB compared to compressing the original uncorrected video.