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Digital Unfading of Chromogenic Film Informed by Its Spectral Densities

Bibliographic Data

ID13125638
AuthorsSreya Chatterjee (0009-0009-3640-4211, HTW Berlin - University of Applied Sciences), Giorgio Trumpy (0000-0001-9534-0507, Norwegian University of Science and Technology, corresponding author), Ulrich Ruedel (HTW Berlin - University of Applied Sciences)
Year2023
Volume6
Issue4
Pages3418-3428
Publication date2023-03-28
Open AccessYes
TypeARTICLE
VenueHeritage (JOURNAL)
Journal identifiersISSN: 2571-9408 • E-ISSN: 2571-9408
PublisherMDPI AG (PUBLISHER • IT)
DOI10.3390/heritage6040181
OpenAlexW4361212245
LanguageEN
References cited14

A material-based approach for the digital restoration of chromogenic photographic and film materials affected by dye fading is proposed. Through a digital reconstruction of the original optical properties, the proposed restoration methodology approximates the original color appearance in a non-subjective manner, thus improving the results compared to conventional RGB tonal re-adjustment of the film scan both in terms of quality and presumed faithfulness to original appearance. In order to do so, the degree of fading is derived from neutral black parts of the film’s image content, and the knowledge of the film material’s spectral densities is used to digitally reconstruct the colors corresponding to the material’s original dye concentrations and render them in an RGB space. For a comparison, results from conventional re-grading were adjusted to render them most similar—and thus comparable—to the results of the proposed spectrally informed digital unfading. The restored images obtained through spectrally informed unfading were deemed clearly superior in terms of color subtlety, color faithfulness and coherence

Algorithm · Chromogenic · Color space · Computer vision · Fading · Image (mathematics · Optics · Physics · RGB color model · Advanced Image Fusion Techniques · Color Science and Applications · Computer Science · Cultural Heritage Materials Analysis · Materials Science · Mathematics · Artificial Intelligence

  • Contributions to the Characterization of Chromogenic Dyes in Color Slides

    Open Access•Joana Silva, A Jorge Parola et al.•Heritage•2022

Highly citedNo

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