Evidence map›Paper›PMID 35630262›Full record

ArticleMicromachines2022

Single-Pixel Near-Infrared 3D Image Reconstruction in Outdoor Conditions.

C Osorio Quero, D Durini, J Rangel-Magdaleno, J Martinez-Carranza, R Ramos-Garcia

Abstract read
In one paragraph

Article in Micromachines, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

C Osorio QueroElectronics Department, Instituto Nacional de Astrofísica, Óptica y Electrónica-INAOE, Calle Luis Enrique Erro 1, Puebla 72840, Mexico.ORCID 0000-0003-4092-127X
D DuriniElectronics Department, Instituto Nacional de Astrofísica, Óptica y Electrónica-INAOE, Calle Luis Enrique Erro 1, Puebla 72840, Mexico.ORCID 0000-0002-5979-1391
J Rangel-MagdalenoElectronics Department, Instituto Nacional de Astrofísica, Óptica y Electrónica-INAOE, Calle Luis Enrique Erro 1, Puebla 72840, Mexico.ORCID 0000-0003-2785-5060
J Martinez-CarranzaComputer Science Department, Instituto Nacional de Astrofísica, Óptica y Electrónica-INAOE, Calle Luis Enrique Erro 1, Puebla 72840, Mexico.ORCID 0000-0002-8914-1904
R Ramos-GarciaOptics Department, Instituto Nacional de Astrofísica, Óptica y Electrónica-INAOE, Calle Luis Enrique Erro 1, Puebla 72840, Mexico.ORCID 0000-0002-2712-4981

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the last decade, the vision systems have improved their capabilities to capture 3D images in bad weather scenarios. Currently, there exist several techniques for image acquisition in foggy or rainy scenarios that use infrared (IR) sensors. Due to the reduced light scattering at the IR spectra it is possible to discriminate the objects in a scene compared with the images obtained in the visible spectrum. Therefore, in this work, we proposed 3D image generation in foggy conditions using the single-pixel imaging (SPI) active illumination approach in combination with the Time-of-Flight technique (ToF) at 1550 nm wavelength. For the generation of 3D images, we make use of space-filling projection with compressed sensing (CS-SRCNN) and depth information based on ToF. To evaluate the performance, the vision system included a designed test chamber to simulate different fog and background illumination environments and calculate the parameters related to image quality.

Indexed as

3D imagingfogHadamard patternsNIRShape-from-Shading (SFS)single-pixel imaging (SPI)Time-of-Flight (ToF)

Identifiers

PMID35630262
PMCPMC9145037

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.