Traditional per-title encoding schemes aim to optimize encoding resolutions to deliver the highest perceptual quality for each representation. However, keeping the encoding time within an acceptable threshold for a smooth user experience is important to reduce the carbon footprint and energy consumption on encoding servers in video streaming applications. Toward this realization, we introduce an encoding latency-a ware dynamic resolution encoding scheme (LADRE) for adaptive video streaming applications. LADRE determines the encoding resolution for each target bitrate by utilizing a random forest-based prediction model for every video segment based on spatiotemporal features and the acceptable target latency. Experimental results show that LADRE achieves an overall average quality improvement of 0.58 dB PSNR and 0.43 dB XPSNR while maintaining the same bitrate, compared to the HTTP Live Streaming (HLS) bitrate ladder encoding of 200 s segments using the VVenC encoder, when the encoding latency for each representation is set to remain below the 200 s threshold. This is accompanied by an 84.17 % reduction in overall encoding energy consumption.

翻译：传统逐视频标题编码方案旨在优化编码分辨率，以在每个表示版本中实现最高感知质量。然而，在视频流传输应用中，将编码时间控制在可接受阈值内以保障流畅用户体验，对于减少编码服务器的碳足迹和能耗至关重要。基于这一目标，我们提出了一种面向自适应视频流传输的编码延迟感知动态分辨率编码方案（LADRE）。LADRE利用基于随机森林的预测模型，根据视频片段的时空特征及可接受的目标延迟，为每个目标码率确定编码分辨率。实验结果表明，与采用VVenC编码器对200秒片段进行HTTP实时流传输（HLS）码率阶梯编码相比，当每个表示版本的编码延迟控制在200秒阈值以下时，LADRE在保持相同码率的前提下，实现了整体平均PSNR提高0.58 dB、XPSNR提高0.43 dB的质量提升，同时总体编码能耗降低了84.17%。