Evidence map›Paper›PMID 41809657›Full record

ArticleRSC advances2026

Rediscovering lost colors: film color restoration by hyperspectral imaging and cluster-based spectral correction algorithm (CBSCA).

Emilio Catelli, Lingxi Liu, Jacopo Fadanni, Jošt Stergar, Matija Milanič, Giorgia Sciutto, Francesco Zerbetto, Silvia Prati

Abstract read
In one paragraph

Article in RSC advances, 2026. 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

8 authors.

Emilio CatelliDepartment of Chemistry "G. Ciamician", University of Bologna, Ravenna Campus Via G. Guaccimanni 42 Ravenna 48121 Italy s.prati@unibo.it.
Lingxi LiuDepartment of Art History, Musicology and Theatre Studies, Ghent University Sint-Pietersnieuwstraat 41 9000 Ghent Belgium.
Jacopo FadanniDepartment of Physics and Astronomy, University of Padova Via F. Marzolo 8 Padova 35131 Italy.ORCID https://orcid.org/0000-0002-3844-5510
Jošt StergarJozef Stefan Institute Jamova cesta 39 Ljubljana SI-1000 Slovenia.
Matija MilaničJozef Stefan Institute Jamova cesta 39 Ljubljana SI-1000 Slovenia.
Giorgia SciuttoDepartment of Chemistry "G. Ciamician", University of Bologna, Ravenna Campus Via G. Guaccimanni 42 Ravenna 48121 Italy s.prati@unibo.it.
Francesco ZerbettoDepartment of Chemistry "G. Ciamician", University of Bologna Via P. Gobetti 85 Bologna 40129 Italy francesco.zerbetto@unibo.it.
Silvia PratiDepartment of Chemistry "G. Ciamician", University of Bologna, Ravenna Campus Via G. Guaccimanni 42 Ravenna 48121 Italy s.prati@unibo.it.ORCID https://orcid.org/0000-0002-9974-731X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The present study proposes a new method for the digital restoration of color films affected by irregular color degradation. Color fading is a major problem affecting analog color films and while most existing digital methods address homogeneous dye fading, the correction of irregular color degradation remains a challenging and time-consuming process. The main objective of this work is to develop a scalable and minimally user-guided strategy capable of restoring such complex degradation patterns. The proposed approach combines visible-range hyperspectral imaging of degraded film frames to obtain detailed spectral information with a novel computational algorithm referred as the Cluster-Based Spectral Correction Algorithm (CBSCA). This algorithm is specifically designed to handle the large volume of data recorded by hyperspectral acquisition, enabling robust color restoration while ensuring reduced computational demand and limited subjective intervention. In comparison with conventional RGB scanners and color restoration software, this approach offers a methodology to perform accurate color acquisition and correction while effectively managing large hyperspectral datasets. The ultimate goal is to recover the film's original visual content, ensuring its accessibility to the public.

Identifiers

PMID41809657
PMCPMC12969991

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LicenceCC BY-NC
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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.