An Efficient Color Encoding Scheme for HDR Video Compression The human visual system does not perceive all colors the same way, being sensitive to changes in some colors more than others. In this work, we propose a chroma processing scheme that takes advantage of this characteristic of the human eye to reduce the color errors generated by the quantization and subsampling processes in the HDR video delivery pipeline. Our method redistributes chroma codewords in favor of those colors that our eyes are most sensitive to. Objective evaluations have shown that the proposed chroma processing can significantly improve the color accuracy of the tested HDR video content. Furthermore, compression performance evaluations showed that the proposed method improves the compression efficiency of the existing approach by 0.6% and 13.3% on average, in terms of tPSNR XYZ and tOSNR XYZ, respectively.

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.