S&M Young Researcher Paper Award 2020
Recipients: Ding Jiao, Zao Ni, Jiachou Wang, and Xinxin Li [Winner's comments]
Paper: High Fill Factor Array of Piezoelectric Micromachined
Ultrasonic Transducers with Large Quality Factor

S&M Young Researcher Paper Award 2021
Award Criteria
Notice of retraction
Vol. 32, No. 8(2), S&M2292

Print: ISSN 0914-4935
Online: ISSN 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Sensors and Materials
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Light Field Acquisition Method Based on Depth Sampling [PDF]

Fuzhou Duan, Ying Zuo, Hongliang Guan, and Tian Guo

(Received July 8, 2021; Accepted September 1, 2021)

Keywords: light field imaging, depth sampling, light field acquisition, clarity evaluation

Light field imaging technology is a new imaging method for recording light propagation. It records light mainly through two devices: a camera array and an all-optical camera. The collected light field data can be processed in different ways such as post hoc on-demand imaging and depth estimation. This technology has high application value in the fields of depth extraction, 3D modeling, and virtual reality, and is one of the hot spots of imaging research. However, existing light field acquisition methods are based on angular sampling, which requires special hardware. The angular and spatial resolutions of the light field collected by these methods are mutually constrained. Accordingly, we propose a new acquisition method for the depth sampling of the light field and compare the clarity of light field subaperture images acquired by this method with that of the images acquired by the traditional angular sampling method. The results of the study show that the spatial resolution of the light field images acquired with depth sampling reaches the sensor’s pixel dimensions without special hardware, and their sharpness is very close to that of light field images acquired by the angular sampling method. This study provides a more concise approach to the acquisition of light field images in computational imaging techniques.

Corresponding author: Ying Zuo, Hongliang Guan

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