Evidence map›Paper›PMID 36590304›Full record

ArticleFrontiers in neuroscience2022

An integrated method for color correction based on color constancy for early mural images in Mogao Grottoes.

Zhen Liu, Yi-Xuan Liu, Gui-Ai Gao, Yong Kong, Bing Wu, Jin-Xing Liang

Open access · goldAbstract read
In one paragraph

Article in Frontiers in neuroscience, 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
0.6field-weighted citation impact, top 33% of its field
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, 4 citations in OpenAlex.

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 at 2 institutions in 1 country.

Zhen LiuSchool of Communication, Qufu Normal University, Rizhao, Shandong, China.
Yi-Xuan LiuSchool of Communication, Qufu Normal University, Rizhao, Shandong, China.
Gui-Ai GaoSchool of Communication, Qufu Normal University, Rizhao, Shandong, China.
Yong KongSchool of Communication, Qufu Normal University, Rizhao, Shandong, China.
Bing WuSchool of Communication, Qufu Normal University, Rizhao, Shandong, China.
Jin-Xing LiangSchool of Computer Science and Artificial Intelligence, Wuhan Textile University, Wuhan, China.
Qufu Normal University · CNWuhan Textile University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Restoring the correct or realistic color of a cultural heritage object is a crucial problem for imaging techniques. Digital images often have undesired color casts due to adverse effects caused by unstable illuminant conditions, vignetting, and color changes due to camera settings. In this work, we present an improved color correction method for color cast images that makes the color appear more realistic. It is based on a computational model of the human visual system that perceives objects by color constancy theory; it realizes illumination non-uniformity compensation and chromaticity correction for color cast images by taking into account the color stability of some pigments. This approach has been used to correct the color in Cave 465 of the Mogao Grottoes. The experimental results demonstrate that the proposed method is able to "adaptively correct" color cast images with widely varying lighting conditions and improve the consistency efficaciously. It can achieve improved consistency in the mean CIEDE2000 color difference compared with the images before correction. This colorimetric correction methodology is sufficiently accurate in color correction implementation for cast images of murals captured in the early years.

Indexed as

color cast correctioncolor constancyDunhuang muralshomomorphic filterillumination non-uniformity

Identifiers

PMID36590304
PMCPMC9798325
OpenAlexW4311792076

What OpenQuestion holds

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LicenceCC BY
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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.