Optimizing framerate for a given bitrate-spatial resolution pair in adaptive video streaming is essential to maintain perceptual quality while considering decoding complexity. Low framerates at low bitrates reduce compression artifacts and decrease decoding energy. We propose a novel method, Decoding-complexity aware Framerate Prediction (DECODRA), which employs a Variable Framerate Pareto-front approach to predict an optimized framerate that minimizes decoding energy under quality degradation constraints. DECODRA dynamically adjusts the framerate based on current bitrate and spatial resolution, balancing trade-offs between framerate, perceptual quality, and decoding complexity. Extensive experimentation with the Inter-4K dataset demonstrates DECODRA's effectiveness, yielding an average decoding energy reduction of up to 13.45%, with minimal VMAF reduction of 0.33 points at a low-quality degradation threshold, compared to the default 60 fps encoding. Even at an aggressive threshold, DECODRA achieves significant energy savings of 13.45% while only reducing VMAF by 2.11 points. In this way, DECODRA extends mobile device battery life and reduces the energy footprint of streaming services by providing a more energy-efficient video streaming pipeline.

翻译：在自适应视频流中，针对给定的码率-空间分辨率组合优化帧率，对于在考虑解码复杂度的同时保持感知质量至关重要。低码率下的低帧率可减少压缩伪影并降低解码能耗。我们提出了一种新颖的解码复杂度感知帧率预测方法（DECODRA），该方法采用可变帧率帕累托前沿方法，在质量退化约束下预测能够最小化解码能耗的优化帧率。DECODRA 根据当前码率和空间分辨率动态调整帧率，平衡帧率、感知质量与解码复杂度之间的权衡。基于 Inter-4K 数据集的大量实验证明了 DECODRA 的有效性：与默认的 60 fps 编码相比，在低质量退化阈值下，该方法平均可降低高达 13.45% 的解码能耗，而 VMAF 仅下降 0.33 分。即使在激进阈值下，DECODRA 仍能实现 13.45% 的显著节能效果，而 VMAF 仅降低 2.11 分。通过这种方式，DECODRA 通过提供更节能的视频流处理流程，延长了移动设备电池寿命并降低了流媒体服务的能耗足迹。