Quality-Driven Dynamic VVC Frame Partitioning for Efficient Parallel Processing

TL;DR

This paper introduces a dynamic frame partitioning method for VVC that optimizes parallel processing by balancing encoding speed and quality, leveraging content texture and previous encoding times.

Contribution

It proposes a novel TRS partitioning approach at the frame level that adapts based on content and encoding history, improving parallelism efficiency.

Findings

Significantly reduces multi-thread encoding time.

Achieves slightly better encoding quality than uniform partitioning.

Demonstrates effectiveness on VVC standard.

Abstract

VVC is the next generation video coding standard, offering coding capability beyond HEVC standard. The high computational complexity of the latest video coding standards requires high-level parallelism techniques, in order to achieve real-time and low latency encoding and decoding. HEVC and VVC include tile grid partitioning that allows to process simultaneously rectangular regions of a frame with independent threads. The tile grid may be further partitioned into a horizontal sub-grid of Rectangular Slices (RSs), increasing the partitioning flexibility. The dynamic Tile and Rectangular Slice (TRS) partitioning solution proposed in this paper benefits from this flexibility. The TRS partitioning is carried-out at the frame level, taking into account both spatial texture of the content and encoding times of previously encoded frames. The proposed solution searches the best partitioning configuration that minimizes the trade-off between multi-thread encoding time and encoding quality loss. Experiments prove that the proposed solution, compared to uniform TRS partitioning, significantly decreases multi-thread encoding time, with slightly better encoding quality.