Evidence map›Paper›PMID 38067704›Full record

ArticleSensors (Basel, Switzerland)2023

Depth Quality Improvement with a 607 MHz Time-Compressive Computational Pseudo-dToF CMOS Image Sensor.

Anh Ngoc Pham, Thoriq Ibrahim, Keita Yasutomi, Shoji Kawahito, Hajime Nagahara, Keiichiro Kagawa

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. 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
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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

6 authors.

Anh Ngoc PhamGraduate School of Integrated Science and Technology, Shizuoka University, Hamamatsu 432-8011, Japan.
Thoriq IbrahimGraduate School of Integrated Science and Technology, Shizuoka University, Hamamatsu 432-8011, Japan.
Keita YasutomiResearch Institute of Electronics, Shizuoka University, Hamamatsu 432-8011, Japan.
Shoji KawahitoResearch Institute of Electronics, Shizuoka University, Hamamatsu 432-8011, Japan.
Hajime NagaharaInstitute of Datability Science, Osaka University, Suita 565-0871, Japan.
Keiichiro KagawaResearch Institute of Electronics, Shizuoka University, Hamamatsu 432-8011, Japan.

Funding

Grants-in-Aid for Scientific Research (S) 17H06102, 18H05240Japan Science and Technology Agency (JST) CREST JPMJCR22C1
6 · The paper itself

Abstract

In this paper, we present a prototype pseudo-direct time-of-flight (ToF) CMOS image sensor, achieving high distance accuracy, precision, and robustness to multipath interference. An indirect ToF (iToF)-based image sensor, which enables high spatial resolution, is used to acquire temporal compressed signals in the charge domain. Whole received light waveforms, like those acquired with conventional direct ToF (dToF) image sensors, can be obtained after image reconstruction based on compressive sensing. Therefore, this method has the advantages of both dToF and iToF depth image sensors, such as high resolution, high accuracy, immunity to multipath interference, and the absence of motion artifacts. Additionally, two approaches to refine the depth resolution are explained: (1) the introduction of a sub-time window; and (2) oversampling in image reconstruction and quadratic fitting in the depth calculation. Experimental results show the separation of two reflections 40 cm apart under multipath interference conditions and a significant improvement in distance precision down to around 1 cm. Point cloud map videos demonstrate the improvements in depth resolution and accuracy. These results suggest that the proposed method could be a promising approach for virtually implementing dToF imaging suitable for challenging environments with multipath interference.

Indexed as

charge-domain time-compressive sensingmultipath interferencepseudo-dToF imaging

Identifiers

PMID38067704
PMCPMC10708863

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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.