Alexandre Mercat

High-dynamic range (HDR) video content has gained popularity due to its enhanced color depth and luminance range, but it also presents new challenges in terms of compression efficiency and energy consumption. In this paper, we present an in-depth study of the compression performance and energy efficiency of HDR video encoding using High-Efficiency Video Coding (HEVC). In addition to using a native 10-bit HDR encoding configuration as a reference, we explore whether applying tone mapping to an 8-bit representation before encoding can result in additional bitrate and energy savings without compromising visual quality. The main contributions of this work are as follows: 1) a detailed evaluation of four HDR video encoding configurations, three of which leverage tone mapping techniques, 2) a comprehensive experimental setup involving over 15,000 individual encodings across three open-source HEVC encoders (Kvazaar, x265, and SVT-HEVC) and multiple presets, 3) the use of two advanced perception-based metrics for BD-rate calculations, one of which is specifically tailored to capture colour distortions and 4) an open-source dataset consisting of all experimental results for further research. Among the three tone-mapping configurations tested, our findings show that a simple bit-shifting approach can achieves significant reductions in both bitrate and energy consumption compared to the native 10-bit HDR encoding configuration. This research aims to lay an initial foundation for understanding the balance between coding efficiency and energy consumption in HDR video encoding, offering valuable insights to guide future advancements in the field.

The significant growth in global video data traffic can be mitigated by saliency-based video coding schemes that seek to increase coding efficiency without any loss of objective visual quality by compressing salient video regions less heavily than non-salient regions. However, conducting salient object detection (SOD) on every video frame before encoding tends to lead to substantial complexity and energy consumption overhead, especially if state-of-the-art deep learning techniques are used in saliency detection. This work introduces a saliency-guided video encoding framework that reduces the energy consumption over frame-by-frame SOD by increasing the detection interval and applying the proposed region-of-interest (ROI) tracking between successive detections. The computational complexity of our ROI tracking technique is kept low by predicting object movements from motion vectors, which are inherently calculated during encoding. Our experimental results demonstrate that the proposed ROI tracking solution saves energy by 86-95% and attains 84-94% accuracy over frame-by-frame SOD. Correspondingly, integrating our proposal into the complete saliency-guided video coding scheme reduces energy consumption on CPU by 79-82% at a cost of weighted PSNR of less than 5%. These findings indicate that our solution has significant potential for low-cost and low-power streaming media applications.

Effective and smooth video communication has become an integral tool for interaction in our modern society. The well-known WebRTC project is optimized for server-based communication architectures with less stringent latency requirements. This paper introduces an open-source, peer-to-peer (P2P) mesh-based application called uvgComm 1.0 for low-latency multi-party video communication. Our experimental results show that uvgComm attains 25% lower latency than server-based solutions at 219 ms. In addition, it offers advanced privacy protection mechanisms with end-to-end encryption and P2P mesh topology that delivers media without any media servers. The ambitious goal of uvgComm is to take P2P mesh-based conferencing architecture to the next level and make this architecture a serious competitor to server-based communication architectures.

Versatile Video Coding (VVC/H.266) standard is the emerging successor to the widespread High Efficiency Video Coding (HEVC/H.265). This work introduces the latest version of our academic open-source VVC intra encoder called uvg266. It has been developed from our well-known Kvazaar HEVC encoder by introducing new VVC coding tools into carefully optimized and parallelized coding flow of Kvazaar. This paper outlines the design methodology and implementation aspects of all intra (AI) configuration of uvg266. The experimental results show that single-threaded uvg266 is more than twice as fast as the state-of-the-art VVenC encoder in all our test cases. In speed-optimized coding, the coding overhead of uvg266 is 21.7% but the gap narrows down to 2.6% in the rate distortion optimized coding case. uvg266 has almost linear speedup with core count up to 32 threads. The better scalability of uvg266 quadruples the speed over VVenC. Furthermore, single-threaded uvg266 is up to 380× as fast as VVC reference software VTM and the gap raises to over 11,000× with 32 threads. To the best of our knowledge, uvg266 is currently the fastest available open-source VVC intra software encoder.