Film based media becomes unstable over time, unless they are stored at low temperatures and the humidity is controlled. Some defects, such as bleaching, are difficult to solve using photochemical restoration methods; in such cases, digital restoration can be an alternative solution. The basic idea of the proposed work is to mimic the robust capabilities of the human vision system (HVS) to set up a tool to filter damaged frames in a partially automated way. In fact, film colour cast, caused by ageing, can be considered as generic chromatic noise, thus a colour constancy method can be suitable for restoring it. Moreover a colour constancy method inspired by the HVS behaviour does not need any a-priori information about the colour cast and its magnitude. Another advantage of HVS inspired algorithms is their local effect since film chemical deterioration is usually non-uniform. Several test have been performed with an algorithm called ACE (Automatic Colour Equalization). The technique, presented here, is not just an application of ACE on movie images, but also an enhancement of ACE principles to meet the requirements of digital film restoration practice. The basic ACE computation extracts autonomously the visual content of the frame, correcting colour cast if present and expanding its dynamic range. This behaviour 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 has not to 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. Examples are presented to discuss characteristics, advantages and limits of the use of perceptual models in digital movies colour restoration.
A human color perception model for film unsupervised digital restoration / A. Rizzi. ((Intervento presentato al convegno The Mathematics and Art of Film Editing and Restoration (IMA) tenutosi a Minneapolis (Minnesota-USA) nel 2006.
A human color perception model for film unsupervised digital restoration
A. RizziPrimo
2006
Abstract
Film based media becomes unstable over time, unless they are stored at low temperatures and the humidity is controlled. Some defects, such as bleaching, are difficult to solve using photochemical restoration methods; in such cases, digital restoration can be an alternative solution. The basic idea of the proposed work is to mimic the robust capabilities of the human vision system (HVS) to set up a tool to filter damaged frames in a partially automated way. In fact, film colour cast, caused by ageing, can be considered as generic chromatic noise, thus a colour constancy method can be suitable for restoring it. Moreover a colour constancy method inspired by the HVS behaviour does not need any a-priori information about the colour cast and its magnitude. Another advantage of HVS inspired algorithms is their local effect since film chemical deterioration is usually non-uniform. Several test have been performed with an algorithm called ACE (Automatic Colour Equalization). The technique, presented here, is not just an application of ACE on movie images, but also an enhancement of ACE principles to meet the requirements of digital film restoration practice. The basic ACE computation extracts autonomously the visual content of the frame, correcting colour cast if present and expanding its dynamic range. This behaviour 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 has not to 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. Examples are presented to discuss characteristics, advantages and limits of the use of perceptual models in digital movies colour restoration.Pubblicazioni consigliate
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.