Evidence map›Paper›PMID 39717119›Full record

ArticleMethodsX2024

Methodological approach for fast high-resolution image selection: FAHRIS algorithm.

Bjørnar Åsebø, Stefano Cavazzani, Chiara Bertolin, Carlo Bettanini, Giampaolo Fusato, Andrea Bertolo, Pietro Fiorentin

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Article in MethodsX, 2024. 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

7 authors.

Bjørnar ÅsebøDepartment of Mechanical and Industrial Engineering, Norwegian University of Science and Technology, Trondheim, Norway.
Stefano CavazzaniDepartment of Mechanical and Industrial Engineering, Norwegian University of Science and Technology, Trondheim, Norway.
Chiara BertolinDepartment of Mechanical and Industrial Engineering, Norwegian University of Science and Technology, Trondheim, Norway.
Carlo BettaniniDepartment of Industrial Engineering, University of Padua, Padua, Italy.
Giampaolo FusatoRegional Environmental Prevention and Protection Agency of Veneto, Padua, Italy.
Andrea BertoloRegional Environmental Prevention and Protection Agency of Veneto, Padua, Italy.
Pietro FiorentinDepartment of Industrial Engineering, University of Padua, Padua, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent research highlights advancements in collecting Artificial Light at Night (ALAN) data using radiosondes on stratospheric balloons, revealing a need for enhanced in-flight image stabilization. This paper proposes a twofold approach: Firstly, it introduces a design concept for a high-resolution image acquisition and stabilization system for aerial instruments (e.g., drones, balloons). Secondly, it presents a novel Fast Algorithm for High-Resolution Image Selection (FAHRIS) for rapid image selection, grouping and stitching of acquired imagery. FAHRIS' effectiveness is validated using datasets from three flights over Italy: a stratospheric balloon flight reaching 34 kms over Florence, and drone flights using a DJI Mavic 2 up to 253 m over Trevisoand 330 m over Padua. Limitations and challenges encountered during the validation of FAHRIS, such as computational constraints affecting dataset processing, are addressed. Additionally, the results of the image stitching process highlight potential distortions and stretching issues, particularly evident in images with significant relative angles.•Design proposition of stabilization system for aerial instruments.•Development of a novel and fast image selection, grouping and stitching algorithm (FAHRIS).•Validation of algorithm against data sets from three flights.

Indexed as

Atmospheric effectsFast Algorithm for High-Resolution Image Selection - FAHRISImage analysisImage classificationImage groupingImage stitchingLight pollutionRadiosondesSite testingUnmanned aerial vehicles

Identifiers

PMID39717119
PMCPMC11664006

What OpenQuestion holds

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LicenceCC BY
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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.