Content Adaptive Wavelet Lifting for Scalable Lossless Video Coding

TL;DR

This paper introduces a content adaptive wavelet lifting method for scalable lossless video coding that dynamically adjusts decomposition depth based on video content, improving visual quality and reducing bit rate.

Contribution

It proposes a novel adaptive wavelet transform that locally varies decomposition levels, enhancing quality and efficiency over traditional fixed-depth methods.

Findings

Up to 10.28 dB quality improvement in lowpass subband

1.06% reduction in bit rate

Effective adaptation to scene changes and motion

Abstract

Scalable lossless video coding is an important aspect for many professional applications. Wavelet-based video coding decomposes an input sequence into a lowpass and a highpass subband by filtering along the temporal axis. The lowpass subband can be used for previewing purposes, while the highpass subband provides the residual content for lossless reconstruction of the original sequence. The recursive application of the wavelet transform to the lowpass subband of the previous stage yields coarser temporal resolutions of the input sequence. This allows for lower bit rates, but also affects the visual quality of the lowpass subband. So far, the number of total decomposition levels is determined for the entire input sequence in advance. However, if the motion in the video sequence is strong or if abrupt scene changes occur, a further decomposition leads to a low-quality lowpass subband. Therefore, we propose a content adaptive wavelet transform, which locally adapts the depth of the decomposition to the content of the input sequence. Thereby, the visual quality of the low-pass subband is increased by up to 10.28 dB compared to a uniform wavelet transform with the same number of total decomposition levels, while the required rate is reduced by 1.06% additionally.