Towards PDE-Based Video Compression with Optimal Masks Prolongated by Optic Flow

Michael Breuß,Georg Radow,Laurent Hoeltgen

doi:10.1007/s10851-020-00973-6

Michael Breuß, Georg Radow + Show 1 more

Open Access

https://doi.org/10.1007/s10851-020-00973-6

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Abstract

Lossy image compression methods based on partial differential equations have received much attention in recent years. They may yield high-quality results but rely on the computationally expensive task of finding an optimal selection of data. For the possible extension to video compression, this data selection is a crucial issue. In this context, one could either analyse the video sequence as a whole or perform a frame-by-frame optimisation strategy. Both approaches are prohibitive in terms of memory and run time. In this work, we propose to restrict the expensive computation of optimal data to a single frame and to approximate the optimal reconstruction data for the remaining frames by prolongating it by means of an optic flow field. In this way, we achieve a notable decrease in the computational complexity. As a proof-of-concept, we evaluate the proposed approach for multiple sequences with different characteristics. In doing this, we discuss in detail the influence of possible computational setups. We show that the approach preserves a reasonable quality in the reconstruction and is very robust against errors in the flow field.

Highlights

Transform-based image and video compression algorithms are still the preferred choice in many applications [33]
It has been shown that partial differential equation (PDE)-based methods represent a viable alternative in the context of image compression
Our work shows that it is possible to replace the expensive frame-wise computation of optimal inpainting data with the simple computation of a displacement field

Summary

Introduction

Transform-based image and video compression algorithms are still the preferred choice in many applications [33]. In order to achieve a competitive level with state-of-the-art codecs, the PDE-based methods require sophisticated data optimisation schemes and fast numerical algorithms. The most important task is the choice of a small subset of pixels, often called mask, from which the original image can be accurately reconstructed by solving a PDE. This data selection problem has proven to be delicate, see [6,8,12,13,22,39] for some strategies considered in the past. Most approaches have resorted to a frame-by-frame consideration Even such a frame-wise tuning can be computationally expensive, especially for longer videos

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