Fast luminance and chrominance correction based on motion compensated linear regression for multiview video coding Luminance and chrominance correction (LCC) is important in multiview video coding (MVC) because it provides better ratedistortion performance when encoding video sequences captured by illcalibrated multiview cameras. This paper presents a robust and fast LCC algorithm based on motion compensated linear regression which reuses the motion information from the encoder. We adopt the linear weighted prediction model in H.264AVC as our LCC model. In our experiments, the proposed LCC algorithm outperforms basic histogram matching method up to 0.4dB with only few computational overhead and zero external memory bandwidth. So, the dataflow of this method is suitable for low bandwidthlow power VLSI design for future multiview applications.

Template based illumination compensation algorithm for multiview video coding Recently multiview video coding (MVC) standard has been finalized as an extension of H.264AVC by Joint Video Team (JVT). In the project Joint Multiview Video Model (JMVM) for the standardization, illumination compensation (IC) is adopted as a useful tool. In this paper, a novel illumination compensation algorithm based on template is proposed. The basic idea of the algorithm is that the illumination of the current block has a strong correlation with its adjacent template. Based on this idea, firstly a template based illumination compensation method is presented, and then a template models selection strategy is devised to improve the illumination compensation performance. The experimental results show that the proposed algorithm can improve the coding efficiency significantly.