Evidence map›Paper›PMID 37763852›Full record

ArticleMicromachines2023

Micro 4D Imaging Sensor Using Snapshot Narrowband Imaging Method.

Wei Jiang, Dingrong Yi, Caihong Huang, Qing Yu, Linghua Kong

Abstract read
In one paragraph

Article in Micromachines, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Wei JiangCollege of Mechanical Engineering and Automation, Huaqiao University, Xiamen 361021, China.ORCID 0000-0002-8970-5888
Dingrong YiCollege of Mechanical Engineering and Automation, Huaqiao University, Xiamen 361021, China.
Caihong HuangCollege of Mechanical Engineering and Automation, Huaqiao University, Xiamen 361021, China.
Qing YuCollege of Mechanical Engineering and Automation, Huaqiao University, Xiamen 361021, China.ORCID 0000-0001-8767-3889
Linghua KongSchool of Mechanical and Automotive Engineering, Fujian University of Technology, Fuzhou 350118, China.

Funding

General Program of Fujian Province Natural Science Foundation 2020J01840Natural Science Foundation of Fujian 2020J02005
6 · The paper itself

Abstract

The spectral and depth (SAD) imaging method plays an important role in the field of computer vision. However, accurate depth estimation and spectral image capture from a single image without increasing the volume of the imaging sensor is still an unresolved problem. Our research finds that a snapshot narrow band imaging (SNBI) method can discern wavelength-dependent spectral aberration and simultaneously capture spectral-aberration defocused images for quantitative depth estimation. First, a micro 4D imaging (M4DI) sensor is proposed by integrating a mono-chromatic imaging sensor with a miniaturized narrow-band microarrayed spectral filter mosaic. The appearance and volume of the M4DI sensor are the same as the integrated mono-chromatic imaging sensor. A simple remapping algorithm was developed to separate the raw image into four narrow spectral band images. Then, a depth estimation algorithm is developed to generate 3D data with a dense depth map at every exposure of the M4DI sensor. Compared with existing SAD imaging method, the M4DI sensor has the advantages of simple implementation, low computational burden, and low cost. A proof-of-principle M4DI sensor was applied to sense the depth of objects and to track a tiny targets trajectory. The relative error in the three-dimensional positioning is less than 7% for objects within 1.1 to 2.8 m.

Indexed as

depth from defocusmicroarrayed spectral filter mosaicmicro-imaging sensorsnapshot imagingspectral and depth imaging

Identifiers

PMID37763852
PMCPMC10536809

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.