Computational Incoherent holographic single-shot plenoptic camera operating in natural light

Project Details

Description

Conventional cameras capture two-dimensional images, even though our world is three-dimensional
(3D). This lack of depth information limits measurements and restricts our understanding of the
complexity of recorded 3D objects and environments.
Holography does not have these shortcomings, as it can record and reproduce the full wavefield of
light, both amplitude and phase information. Unfortunately, holography relies on light interference,
requiring highly coherent light. That is why holograms are typically recorded in controlled laboratory
conditions with, e.g., lasers.
However, this limitation can be overcome. An incoherent holographic camera prototype was recently
demonstrated using birefringent materials, decomposing incoherent light into mutually interfering
coherent wavefronts. This proof-of-concept system could record color holograms with both sunlight
and indoor lighting.
This would allow for plenoptic 3D information encoding with natural light, enabling post-capture
numerical refocusing and view extraction without a spatio-angular trade-off, and the content can be
shown on a holographic display.
Nonetheless, these holograms are still noisy and of limited quality. This is due to, i.a., low light
efficiency, bulky optics, inaccurate incoherent light propagation models, and the absence of
underlying 3D scene representations.
This research proposal addresses these challenges by developing a computational incoherent
holographic camera with specially designed optics.
1494 / 1500
Co
AcronymFWOAL1101
StatusActive
Effective start/end date1/01/2431/12/27

Keywords

  • incoherent holography
  • computational imaging
  • plenoptic imaging

Flemish discipline codes in use since 2023

  • Photonics, light and lighting
  • Image processing
  • Classical and physical optics
  • Analogue and digital signal processing

Fingerprint

Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.