Fabrice Leleannec

prediction-guided quantization for video tone mapping

Tone Mapping Operators (TMOs) compress High Dynamic Range (HDR) content to address Low Dynamic Range (LDR) displays. However, before reaching the end-user, this tone mapped content is usually compressed for broadcasting or storage purposes. Any TMO includes a quantization step to convert floating point values to integer ones. In this work, we propose to adapt this quantization, in the loop of an encoder, to reduce the entropy of the tone mapped video content. Our technique provides an appropriate quantization for each mode of both the Intra and Inter-prediction that is performed in the loop of a block-based encoder. The mode that minimizes a rate-distortion criterion uses its associated quantization to provide integer values for the rest of the encoding process. The method has been implemented in HEVC and was tested over two different scenarios: the compression of tone mapped LDR video content (using the HM10.0) and the compression of perceptually encoded HDR content (HM14.0). Results show an average bit-rate reduction under the same PSNR for all the sequences and TMO considered of 20.3% and 27.3% for tone mapped content and 2.4% and 2.7% for HDR content.

Efficient implementation of enhanced multiple transforms for video coding

Recently, the advances in transform coding have contributed to significant bitrate saving for the next generation of video coding. In particular, the combination of different discrete trigonometric transforms (DTT’s) was adopted in the Joint Video Exploration Team (JVET) solution, as well as the Bench-Mark Set (BMS) of the future video coding standard (Versatile Video Coding), to efficiently model the residual signal statistics and to improve the overall coding efficiency. However, this combination of transforms necessitates an increase in the memory requirement as well as coding complexity, which could potentially limit their practical use. In this paper, we solve both memory and complexity issues by reducing the number of transforms, where some of the transforms are generated from other by simple mathematical operations, like sign changing and reverse ordering. The simulation results showed that this approach achieves competitive results with substantial simplification of the transform design.