Per Clip Lagrangian Multiplier Optimisation for HEVC

Abstract

The majority of internet traffic is video content. This drives the demand for video compression in order to deliver high quality video at low target bitrates. This paper investigates the impact of adjusting the rate distortion equation on compression performance. An constant of proportionality, k, is used to modify the Lagrange multiplier used in H.265 (HEVC). Direct optimisation methods are deployed to maximise BD-Rate improvement for a particular clip. This leads to up to 21% BD-Rate improvement for an individual clip. Furthermore we use a more realistic corpus of material provided by YouTube. The results show that direct optimisation using BD-rate as the objective function can lead to further gains in bitrate savings that are not available with previous approaches.

References in corpus (1)

• YouTube UGC Dataset for Video Compression Research

Cited by in corpus (4)

• Near Optimal Per-Clip Lagrangian Multiplier Prediction in HEVC
• Per-clip and per-bitrate adaptation of the Lagrangian multiplier in video coding
• Direct Optimisation of $\mathbf{\lambda }$ for HDR Content Adaptive Transcoding in AV1
• Subjective assessment of the impact of a content adaptive optimiser for compressing 4K HDR content with AV1