Computational Integral Imaging Reconstruction via Elemental Image Blending without Normalization.
computational integral imaging reconstruction
integral imaging
Journal
Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366
Informations de publication
Date de publication:
09 Jun 2023
09 Jun 2023
Historique:
received:
07
05
2023
revised:
28
05
2023
accepted:
07
06
2023
medline:
10
7
2023
pubmed:
8
7
2023
entrez:
8
7
2023
Statut:
epublish
Résumé
This paper presents a novel computational integral imaging reconstruction (CIIR) method using elemental image blending to eliminate the normalization process in CIIR. Normalization is commonly used in CIIR to address uneven overlapping artifacts. By incorporating elemental image blending, we remove the normalization step in CIIR, leading to decreased memory consumption and computational time compared to those of existing techniques. We conducted a theoretical analysis of the impact of elemental image blending on a CIIR method using windowing techniques, and the results showed that the proposed method is superior to the standard CIIR method in terms of image quality. We also performed computer simulations and optical experiments to evaluate the proposed method. The experimental results showed that the proposed method enhances the image quality over that of the standard CIIR method, while also reducing memory usage and processing time.
Identifiants
pubmed: 37420635
pii: s23125468
doi: 10.3390/s23125468
pmc: PMC10301616
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : Sangmyung University
ID : 2021 research Grant from Sangmyung University
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