Image and video compression of fluid flow data

TL;DR

This paper evaluates multimedia image and video compression techniques like JPEG, JPEG2000, H.264, H.265, and AV1 for fluid flow data, demonstrating their ability to significantly reduce data size while preserving flow physics.

Contribution

It introduces the application of modern multimedia compression algorithms to fluid flow data, comparing their performance with traditional methods like POD.

Findings

AV1 and H.265 outperform traditional techniques in various flow regimes.

Compression techniques preserve dominant flow features with negligible error.

These algorithms are scalable and suitable for fluid dynamics data storage and transfer.

Abstract

We study the compression of spatial and temporal features in fluid flow data using multimedia compression techniques. The efficacy of spatial compression techniques, including JPEG and JPEG2000 (JP2), and spatio-temporal video compression techniques, namely H.264, H.265, and AV1, in limiting the introduction of compression artifacts and preserving underlying flow physics are considered for laminar periodic wake around a cylinder, two-dimensional turbulence, and turbulent channel flow. These compression techniques significantly compress flow data while maintaining dominant flow features with negligible error. AV1 and H.265 compressions present the best performance across a variety of canonical flow regimes and outperform traditional techniques such as proper orthogonal decomposition in some cases. These image and video compression algorithms are flexible, scalable, and generalizable holding potential for a wide range of applications in fluid dynamics in the context of data storage and transfer.