# Evaluation of 4D Light Field Compression Methods

## TL;DR

This paper evaluates how state-of-the-art image and video compression methods, including AV1 and XVC, perform on 4D light field data, demonstrating significant compression potential while maintaining visual quality.

## Contribution

It extends existing compression methods into 3D and 4D for light fields and compares their effectiveness, identifying the most suitable approach for light field data.

## Key findings

- 4D light field data can be compressed more than independent images.
- Certain video compression standards outperform traditional image codecs.
- Extended compression methods maintain visual quality at high compression ratios.

## Abstract

Light field data records the amount of light at multiple points in space, captured e.g. by an array of cameras or by a light-field camera that uses microlenses. Since the storage and transmission requirements for such data are tremendous, compression techniques for light fields are gaining momentum in recent years. Although plenty of efficient compression formats do exist for still and moving images, only a little research on the impact of these methods on light field imagery is performed. In this paper, we evaluate the impact of state-of-the-art image and video compression methods on quality of images rendered from light field data. The methods include recent video compression standards, especially AV1 and XVC finalised in 2018. To fully exploit the potential of common image compression methods on four-dimensional light field imagery, we have extended these methods into three and four dimensions. In this paper, we show that the four-dimensional light field data can be compressed much more than independent still images while maintaining the same visual quality of a perceived picture. We gradually compare the compression performance of all image and video compression methods, and eventually answer the question, "What is the best compression method for light field data?".