Perceptual Vector Quantization For Video Coding

TL;DR

This paper introduces a perceptual vector quantization method for video coding that conserves energy to better preserve textures, resulting in significant bitrate reductions compared to scalar quantization.

Contribution

It applies gain-shape vector quantization to video encoding, leveraging energy conservation principles from audio coding to improve texture preservation and reduce bitrate.

Findings

Achieves an average of 0.90 dB improvement on still images.

Reduces bitrate by approximately 24.8% at equal quality for images.

Improves video compression efficiency by about 13.7%.

Abstract

This paper applies energy conservation principles to the Daala video codec using gain-shape vector quantization to encode a vector of AC coefficients as a length (gain) and direction (shape). The technique originates from the CELT mode of the Opus audio codec, where it is used to conserve the spectral envelope of an audio signal. Conserving energy in video has the potential to preserve textures rather than low-passing them. Explicitly quantizing a gain allows a simple contrast masking model with no signaling cost. Vector quantizing the shape keeps the number of degrees of freedom the same as scalar quantization, avoiding redundancy in the representation. We demonstrate how to predict the vector by transforming the space it is encoded in, rather than subtracting off the predictor, which would make energy conservation impossible. We also derive an encoding of the vector-quantized codewords that takes advantage of their non-uniform distribution. We show that the resulting technique outperforms scalar quantization by an average of 0.90 dB on still images, equivalent to a 24.8% reduction in bitrate at equal quality, while for videos, the improvement averages 0.83 dB, equivalent to a 13.7% reduction in bitrate.