Computational Integral Imaging Reconstruction via Elemental Image Blending without Normalization

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...

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Bibliographic Details
Main Authors: Eunsu Lee, Hyunji Cho, Hoon Yoo
Format: Article
Language:English
Published: MDPI AG 2023-06-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/23/12/5468
Description
Summary: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.
ISSN:1424-8220