The project aim will be addressed through five Work Packages (WP) delivering objectives.
The project will be pursued at the University of Amsterdam (UvA), the beneficiary of this project, in collaboration with the University of Milan (UniMi), the Eye Filmmuseum of Amsterdam (EYE)
and the Film Center of Sarajevo (FCS) and will last 18 Months.
The DREAM-Film project is mainly focused on the development of research in the film restoration domain (WP2),
with the support of the researcher's training (WP1), knowledge dissemination (WP3) and communication (WP4).
The DREAM-Film project focuses on digitisation , film colour reconstruction and quality assessment, aiming to reconsider these practices given a more inclusive approach,
improving the current state-of-the-art, and focusing on the archives which work under different mandates.
First, the researcher will focus on the Research Questions (RQs):
How much do we know about film restoration practices?
Is it possible to develop a restoration shared methodology considering different archival needs?
To address these RQs, the researcher will conduct a scientific investigation of the current restoration workflow at EYE and FCS. The researcher will develop tests and experiments to perform at
different steps of the restoration workflow, allowing knowledge improvement of the archives' minimum and maximum requirements considering their different societal, cultural and geographical environments.
From this analysis, it will be possible to setup digitisation and restoration standard features to satisfy specific archival needs and define a shared digitisation and restoration methodology,
considering the archival different resources and infrastructures.
At this point the researcher will focus on the RQ:
Can we improve the current film restoration workflow with alternative software and algorithms?
With the supervisor's and co-supervisors' support, the researcher will design a customisable software to automatically perform film colour restoration and an objective image quality assessment.
The DREAM-Film software will include image enhancement algorithms from the literature and the new ReFilm algorithm . ReFilm will be a novel method to reconstruct image film colours
based on the analogue film material properties, the specific archival needs, and the simulation of the Human Visual System (HVS) behaviour. Colour is the product of the light-matter interaction
interpreted by HVS ; thus, colour does not exist without an observer. In recent years, the researchers from UniMi took advantage of the study of human colour vision to develop an innovative method to
enhance digital image colours based on some features of the HVS. Based on Land's Retinex model , this approach enhances colours depending on the scene content, simulating colour appearance. The ReFilm
algorithm will combine the Retinex colour vision model (Re) with film material analysis (Film), in an automatic colour reconstruction procedure that could enhance digital film frames being faithful to
the analogue while simulating the original scene colour appearance. The union of the ReFilm algorithm with a selection of image enhancement algorithms from the literature in a single software will provide
the restorer with a set of automatic, objective and controlled methods to perform colour restoration, making this procedure more consistent and reliable.
DREAM-Film software will also implement a protocol of image quality assessment based on a literature review. This protocol will allow an objective comparison among current and alternative
restoration methods, supporting the user in taking restoration decisions.
The research outputs will be concrete solutions for archivists, researchers, professionals and scholars to obtain consistent digitisation, restoration and quality assessment results over time and across
different laboratories/archives. This will allow institutional and non-institutional archives to have comparable and measurable results. Another direct consequence of the project's outputs will be the
substantial reduction of digitisation and restoration costs in time and resources. Consequently, this will increase the (digitally) accessible audiovisual material with democratisation and inclusiveness.
Plutino A., Bellotti S. and Sasso G., “Finding Harmony in Converging Film Frames into Digital”, Journal of Film Preservation (Open Access),
Issue: 111, 2024, 0009185408422fd1cc18f.
Plutino A., "Color systems for motion picture film digitization: A critical review" (Open Access), Color Research and Application, 2024; 1-9,
DOI: 10.1002/col.22946.
Plutino A., Gaia M., and Ahmedhodzic E., “The A.V. Archives and the Cost of Digital Preservation After the 2020s”,
The (Un)bearable Lightness of Media: Critical Approaches to Sustainability in Film and Audiovisual Production, Circulation and Preservation,
pp 181-187, ISBN: 9788869774737, ISSN: 2420-9570, Mimesis, 2024.
Plutino A., ""Less is More": How Understanding the Process of Motion Picture Film Scanning Can Make Your Life Easier" (Open Access),
in Archiving Conference, 2024, pp 23 - 27, DOI: issn.2168-3204.2024.21.1.5
Plutino A., Bagnati M. and Rizzi A., “Camera Dynamic Range Measurement: The Role of Lenses and Target Spatial Distribution” (OpenAccess), IEEE Transactions on Instrumentation and Measurement (Volume: 73),
2024, DOI: 10.1109/TIM.2024.3400303
Longoni M., Scipioni S., Plutino A., Sarti B., Rizzi A. and Bruni S.,
“Chromogenic dyes in motion picture films at the turn of the 20th and 21st centuries: a multi-technique comparative study“, Microchemical Journal (199), 2024,
DOI: 10.1016/j.microc.2024.110120.
Gaspani M. F., Sarti B., Plutino A. and Rizzi A.,
“Early Cinema: spectral and colorimetric analysis of Tinting dyes for film restoration”, in: Cherubini F. and Muco A., Color and Colorimetry. Multidisciplinary Contributions Vol. XVIII A (Open Access),
pp. 257 – 264, DOI: 10.23738/RCASB.009, ISBN: 978-8-899513-22-1, ISSN: 2785-115X, 2023.
Thielemann C., Armellin L., Sarti B., and Plutino A.,
“Ozaphan films: preliminary study on color analysis and digitization”, in: Cherubini F. and Muco A., Color and Colorimetry. Multidisciplinary Contributions Vol. XVIII A (Open Access),
pp. 249 – 256, DOI: 10.23738/RCASB.009, ISBN: 978-8-899513-22-1, ISSN: 2785-115X, 2023.
Longoni M., Scipioni S., Plutino A., Sarti B., Rizzi A. and Bruni S.,
“Towards the identification of original dyes in chromogenic films: the development of an approach based on chemical analysess”, in: Cherubini F. and Muco A., Color and Colorimetry.
Multidisciplinary Contributions Vol. XVIII A (Open Access), pp. 228 – 231, DOI: 10.23738/RCASB.009, ISBN: 978-8-899513-22-1, ISSN: 2785-115X, 2023.
Plutino A. and Tarini M.,
"Fast ACE (FACE): An Error-Bounded Approximation of Automatic Color Equalization," IEEE Transactions on Image Processing, vol. 32, pp. 2786-2799, 2023,
DOI: 10.1109/TIP.2023.3270770
Sarti B., Plutino A., Crespi A., Morabito G., Rizzi A.,
“FiRe2: an online database for photographic and cinematographic film technical data”, Journal on Computing and Cultural Heritage, 2022,
DOI: 10.1145/3532520
Plutino A., Barricelli B. R., Casiraghi E., Rizzi A.,
“Scoping review on automatic color equalization algorithm”, J. Electron. Imaging 30(2), 020901 (2021),
DOI: 10.1117/1.JEI.30.2.020901
Plutino A., Simone G., Sarti B. and Rizzi A.,
“Movie barcode as support for video analysis and film restoration” (OpenAccess),
SCIentific RESearch and Information Technology (SCIRES), Vol. 11, Issue 2, pp. 33-40, 2021,
DOI: 10.2423/i22394303v11n2p33
Plutino A., Crespi A., Morabito G., Sarti B. and Rizzi A.,
“FiRe2: a Call for a Film Repository of Technical Data and Memories for Photo and Movie Restoration” (OpenAccess),
Cinergie, Special issue Film Heritage and Digital Scholarship: Computer-Based Approaches to Film Archiving, Restoration and Philology, Vol. 2021(20), pp. 69-83, 2021,
DOI: 10.6092/issn.2280-9481/13106.
Plutino A., Rizzi A.,
“Research directions in color movie restoration”, Coloration Technol, Volume 137, Issue 1, Special Issue: Challenges and Open Problems in Colorimetry Special Issue, February 2021, Pages 78-82,
DOI: https://doi.org/10.1111/cote.12488.
Signoroni A., Conte M., Plutino A. and Rizzi A.,
“Spatial-spectral evidence of glare influence on hyperspectral acquisitions”, Sensors 2020, 20(16), 4374;
DOI: 10.3390/s20164374.
Plutino A., Lanaro M. P., Liberini S. and Rizzi A., “Work Memories in Super 8: searching a frame quality metric for movie restoration assessment”,
journal of Cultural Heritage 41 (2020): 238-248, DOI: https://doi.org/10.1016/j.culher.2019.06.008.