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Depth-Assisted Demosaicing for Light Field Data in Layered Object Space
Mittuniversitetet, Fakulteten för naturvetenskap, teknik och medier, Institutionen för informationssystem och –teknologi. (Realistic3D)
Mittuniversitetet, Fakulteten för naturvetenskap, teknik och medier, Institutionen för informationssystem och –teknologi. (Realistic3D)
2019 (engelsk)Inngår i: 2019 IEEE International Conference on Image Processing (ICIP), IEEE, 2019, s. 3746-3750, artikkel-id 8803441Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Light field technology, which emerged as a solution to the increasing demands of visually immersive experience, has shown its extraordinary potential for scene content representation and reconstruction. Unlike conventional photography that maps the 3D scenery onto a 2D plane by a projective transformation, light field preserves both the spatial and angular information, enabling further processing steps such as computational refocusing and image-based rendering. However, there are still gaps that have been barely studied, such as the light field demosaicing process. In this paper, we propose a depth-assisted demosaicing method for light field data. First, we exploit the sampling geometry of the light field data with respect to the scene content using the ray-tracing technique and develop a sampling model of light field capture. Then we carry out the demosaicing process in a layered object space with object-space sampling adjacencies rather than pixel placement. Finally, we compare our results with state-of-art approaches and discuss about the potential research directions of the proposed sampling model to show the significance of our approach.

sted, utgiver, år, opplag, sider
IEEE, 2019. s. 3746-3750, artikkel-id 8803441
Emneord [en]
Lenses, Cameras, Image color analysis, Three-dimensional displays, Microoptics, Interpolation, Two dimensional displays, Light field, demosaicing, object space, ray-tracing technique
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Identifikatorer
URN: urn:nbn:se:miun:diva-37690DOI: 10.1109/ICIP.2019.8803441Scopus ID: 2-s2.0-85076819023ISBN: 978-1-5386-6249-6 (tryckt)OAI: oai:DiVA.org:miun-37690DiVA, id: diva2:1370490
Konferanse
2019 IEEE International Conference on Image Processing (ICIP), Taipei, Taiwan, 22-25 September, 2019
Tilgjengelig fra: 2019-11-15 Laget: 2019-11-15 Sist oppdatert: 2020-01-15bibliografisk kontrollert

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