Simultaneous Color Restoration and Depth Estimation in Light Field Imaging
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Otros documentos de la autoría: Pla, Filiberto; Li, Yongwei; Sjostrom, Marten; Fernandez-Beltran, Ruben
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Mostrar el registro completo del ítemcomunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/160292
comunitat-uji-handle3:10234/160293
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Título
Simultaneous Color Restoration and Depth Estimation in Light Field ImagingFecha de publicación
2022-05-03Cita bibliográfica
Li, Y., Pla, F., Sjöström, M., & Fernandez-Beltran, R. (2022). Simultaneous Color Restoration and Depth Estimation in Light Field Imaging. IEEE Access, 10, 49599-49610Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
https://ieeexplore.ieee.org/document/9766347Versión
info:eu-repo/semantics/publishedVersionPalabras clave / Materias
Resumen
Recent studies in the light field imaging have shown the potential and advantages of different light field information processes. In most of the existing techniques, the processing pipeline of light field has been ... [+]
Recent studies in the light field imaging have shown the potential and advantages of different light field information processes. In most of the existing techniques, the processing pipeline of light field has been treated in a step-by-step manner, and each step is considered to be independent from the others. For example, in light field color demosaicing, inferring the scene geometry is treated as an irrelevant and negligible task, and vice versa. Such processing techniques may fail due to the inherent connection among different steps, and result in both corrupted post-processing and defective pre-processing results. In this paper, we address the interaction between color interpolation and depth estimation in light field, and propose a probabilistic approach to handle these two processing steps jointly. This probabilistic framework is based on a Markov Random Fields —Collaborative Graph Model for simultaneous Demosaicing and Depth Estimation (CGMDD)—to explore the color-depth interdependence from general light field sampling. Experimental results show that both image interpolation quality and depth estimation can benefit from their interaction, mainly for processes such as image demosaicing which are shown to be sensitive to depth information, especially for light field sampling with large baselines. [-]
Publicado en
IEEE Access ( Volume: 10, 49599 - 49610)Datos relacionados
https://ieeexplore.ieee.org/document/9766347/figuresEntidad financiadora
Generalitat Valenciana | Spanish Ministry of Science | Marie Sklodowska-Curie European Training Network on Full Parallax Imaging
Código del proyecto o subvención
AICO-2020-018 | RED2018-102511-T | 676401
Derechos de acceso
info:eu-repo/semantics/openAccess
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