Interpolation-Aware Bitrate Ladder Optimization for Variable Framerate Video Streaming

Amritha Premkumar, Christian Herglotz

Chair of Computer Engineering, Brandenburg University of Technology Cottbus-Senftenberg, Germany

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Abstract: Conventional per-title encoding optimizes encoding parameters over resolution and bitrate while keeping the framerate fixed, which limits adaptability for content with diverse motion characteristics. This paper explores a dynamic framerateaware per-title encoding framework that extends conventional encoding pipelines by incorporating framerate as an explicit optimization dimension. At a fixed resolution, we encode each video at multiple framerates and bitrates. At the decoder side, the lower-framerate encodes are temporally upsampled to the original framerate using real-time frame interpolation methods, such as frame duplication, linear interpolation, and motion-compensated interpolation. We integrate this into a comprehensive end-to-end encoding and evaluation pipeline, comparing the resulting bitrate ladders against conventional fixed-framerate ladders. Experimental results using videos from the Inter4K dataset show that the ladder with Real-Time Intermediate Flow Estimation achieves an average of 15.37 % and 9.89 % bitrate reduction to yield the same PSNR and VMAF, respectively, while increasing the average decoding time by 14.62 %, demonstrating the effectiveness and runtime complexity-quality enhancement tradeoffs of interpolation-aware framerate adaptation for streaming.