Perceptual Color Film Restoration

Metadata

Publisher: SMPTE — White Plains, NY, USA
Doc Type: Journal Article
Content Type: Original Research
Abbreviated Title: SMPTE Mot. Imag. J
Volume: 119, No. 8, pp. 33–41
Abstract: The cinematographic archives represent an important part of our collective memory. In the 1950s, monopack color film became the standard on which millions of cinematographic works were recorded. A couple of decades later, it turned out that this process was chemically unstable, causing the fading of whole film stocks with time. Since the bleaching phenomenon is irreversible, photochemical restoration of faded prints is not possible, hence the incontestability of digital color restoration. Usually, a bleached color release print is the only available record of a film, and no reference color is available; thus, color and dynamic range digital restoration is dependent on historical researches and on the skill of trained technicians who are able to control the restoration parameters. This can lead to a long and frustrating restoration process. For this reason, a restoration tool is a balance between a large number of complex restoration functions used to obtain accuracy in the result and a limit on the number of these functions to maintain simplicity in their use. As an alternative solution, we start from the robust capabilities of the human vision system (HVS) to propose a tool to filter damaged frames in a quasi-unsupervised way. In fact, film color cast, caused by aging, can be considered as generic chromatic noise, and thus a spatial color synthesis algorithm can be suitable for restoring it. Moreover, a method inspired by the HVS behavior does not need any a priori information about the color cast and its magnitude. Several tests have been performed with an algorithm called ACE (Automatic Colour Equalization). ACE is just one of the phases of the restoration pipeline, and it has been modified to meet the requirements of digital film restoration practice. The basic ACE computation autonomously extracts the visual content of the frame, correcting color cast if present and expanding its dynamic range. However, this behavior is not always a good restoring solution: There are cases in which the cast has to be maintained (e.g., underwater shots) or the dynamic range must not be expanded (e.g., sunset or night shots). To this aim, new functions have been added to preserve the natural histogram shape, adding new efficacy in the restoration process. Last, to complete the set, other functions have been added to obtain satisfactory results in cases where an input frame has been excessively corrupted. Examples are presented to discuss characteristics, advantages, and limits for the use of perceptual models in digital movie color restoration.
Publication Date: 2010-11-01
DOI: 10.5594/J17295
ISSN: Print: 1545-0279 | Electronic: 2160-2492
Link: https://doi.org/10.5594/J17295
Author(s): Alessandro RizziUniversity of Milano, University of Brescia (Italy).
bio
Alessandro Rizzi graduated with a degree in computer science from the University of Milano and a Ph.D. in information engineering from the University of Brescia (Italy). He has taught information systems and computer graphics at the University of Brescia and at the Politecnico di Milano and is currently an associate professor and senior research fellow in the Department of Information and Communication (DICo) at the University of Milano, teaching multimedia and digital imaging. Since 1990, Rizzi has been conducting research in the field of color, digital imaging and vision. His main research topic is the use of color information in digital images with particular attention to color perception mechanisms. Rizzi is on the program committee of several conferences on color and digital imaging and is the author of more than 200 papers. He is a founder of the Italian Color Group (2005).
Majed ChambahUniversitŽ de Nice Sophia Antipolis, UniversitŽ de La Rochelle in France.
bio
Majed Chambah has an engineering degree in computer science, a M.Sc. degree in imaging from UniversitŽ de Nice Sophia Antipolis, and a Ph.D. in computer science from UniversitŽ de La Rochelle in France. He works as a lecturer at the UniversitŽ of Reims Champagne Ardenne and is currently head of the GACO Department (Department of Management). Chambah is a color imaging scientist at CReSTIC (Centre de Recherche en Science and Technology of Information and Communication) in Reims, France. His current research interests are color constancy, image enhancement, perceptual imaging and image quality. He is a participant on the program committee and serves as a reviewer of several color imaging conferences and journals.
Copyright: © 2010 Society of Motion Picture and Television Engineers, Inc.

Bibliographic Reference(s)

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<span class="citation">Alessandro Rizzi and Majed Chambah; <cite>Perceptual Color Film Restoration</cite>, SMPTE Motion Imaging Journal ( Volume: 119, Issue: 8, 2010); SMPTE, 2010. Available at <a href="https://doi.org/10.5594/J17295" target="_blank" rel="noopener">https://doi.org/10.5594/J17295</a></span>

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Alessandro Rizzi and Majed Chambah; Perceptual Color Film Restoration, SMPTE Motion Imaging Journal ( Volume: 119, Issue: 8, 2010); SMPTE, 2010
doi: 10.5594/J17295
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Alessandro Rizzi and Majed Chambah; <cite id="bib-10-5594-j17295">Perceptual Color Film Restoration</cite>, SMPTE Motion Imaging Journal ( Volume: 119, Issue: 8, 2010); SMPTE, 2010
<span class="doi">10.5594/J17295</span>
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