Evaluation of 4D Light Field Compression Methods
| Autor: | David Barina, Tomas Chlubna, Pavel Zemcik, Drahomir Dlabaja, Marek Solony |
|---|---|
| Přispěvatelé: | Skala, Václav |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
FOS: Computer and information sciences
Exploit Computer science ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 02 engineering and technology Compression method ztrátová komprese Image (mathematics) Computer Science - Graphics lossy compression Compression (functional analysis) plenoptic imaging FOS: Electrical engineering electronic engineering information engineering 0202 electrical engineering electronic engineering information engineering light field Computer vision změna zaměření obrazu světelné pole business.industry Image and Video Processing (eess.IV) 020207 software engineering Electrical Engineering and Systems Science - Image and Video Processing Graphics (cs.GR) Multimedia (cs.MM) image refocusing Transmission (telecommunications) plicní zobrazení 020201 artificial intelligence & image processing Artificial intelligence business Computer Science - Multimedia Light field Data compression Image compression |
| Popis: | 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?". accepted for publication and presentation at the WSCG 2019 |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|