Spatiotemporal Adaptive Quantization for Video Compression Applications

TL;DR

This paper introduces a novel spatiotemporal adaptive quantization method for video compression that improves rate-distortion performance by considering chroma variance and temporal information, reducing bitrate and encoding time.

Contribution

It extends adaptive quantization by incorporating chroma variance and temporal cues, along with a lambda refined QP technique to lower complexity in rate-distortion optimization.

Findings

Achieves up to 23.1% BD-Rate reduction in Y component.

Reduces encoding time by up to 4.4%.

Effective across various chroma subsampling formats.

Abstract

JCT-VC HEVC HM 16 includes a Coding Unit (CU) level adaptive Quantization Parameter (QP) technique named AdaptiveQP. It is designed to perceptually adjust the QP in Y, Cb and Cr Coding Blocks (CBs) based only on the variance of samples in a luma CB. In this paper, we propose an adaptive quantisation technique that consists of two contributions. The first contribution relates to accounting for the variance of chroma samples, in addition to luma samples, in a CU. The second contribution relates to accounting for CU temporal information as well as CU spatial information. Moreover, we integrate into our method a lambda refined QP technique to reduce complexity associated multiple QP optimizations in the Rate Distortion Optimization process. We evaluate the proposed technique on 4:4:4, 4:2:2, 4:2:0 and 4:0:0 YCbCr test sequences, for which we quantify the results using the Bjontegaard Delta Rate (BD-Rate) metric. Our method achieves a maximum BD-Rate reduction of 23.1% (Y), 26.7% (Cr) and 25.2% (Cb). Furthermore, a maximum encoding time reduction of 4.4% is achieved.