# Compressing Flow Fields with Edge-aware Homogeneous Diffusion Inpainting

## TL;DR

This paper introduces a novel lossy diffusion-based codec for compressing dense 2D flow fields, utilizing coarse grid vectors and edge-aware inpainting to achieve high compression ratios with good quality.

## Contribution

It presents the first diffusion-based compression method for flow fields that preserves edges and discontinuities effectively.

## Key findings

- Achieves compression ratios up to 800:1
- Maintains high quality with simple diffusion inpainting
- Incorporates edge information as boundary conditions

## Abstract

In spite of the fact that efficient compression methods for dense two-dimensional flow fields would be very useful for modern video codecs, hardly any research has been performed in this area so far. Our paper addresses this problem by proposing the first lossy diffusion-based codec for this purpose. It keeps only a few flow vectors on a coarse grid. Additionally stored edge locations ensure the accurate representation of discontinuities. In the decoding step, the missing information is recovered by homogeneous diffusion inpainting that incorporates the stored edges as reflecting boundary conditions. In spite of the simple nature of this codec, our experiments show that it achieves remarkable quality for compression ratios up to 800 : 1.