Digital Film Restoration


Activities concern several aspects of digital film restoration, including the analysis of issues related to the problem, ranging from the kind of different defects to their causes, and to methods and algorithms for their removal. Particular attention is given to some specific types of defects that can affect digital image sequences and to methodologies adopted for their management, devising new machine learning based algorithms and methodologies for their removal. Defects taken into consideration include dust and dirt and linear scratches.

Main achievements

We have proposed methods for automatic removal of linear scratches in digital image sequences, based on the idea of adopting an image model as simple as possible, evaluating the displacement of such model from the real model, and correcting scratch removal through the addition of the computed displacement.

Moreover, we devised a method for the detection and the removal of linear blue scratches that also affect modern color movies, based on specific characteristics of such kind of defect.

We also proposed a new methodology for the solution of classes of problems related to digital film restoration that is well suited for implementation into high-performance parallel and distributed computing environments. The basic idea is to adopt several well-settled algorithms for the class of problems at hand and to combine obtained results through the adoption of suitable image fusion techniques, with the aim of taking advantage of adopted algorithms potentialities and at the same time reducing their disadvantages (see an extended description).

Main collaborations

The research is conducted in collaboration with the Computer Vision and Pattern Recognition Laboratory (CVPRLab) of the University of Naples Parthenope.

Useful/downloadable material

- GC06BlueScratches: Page created to show the images used for testing of the blue scratch detection and removal algorithms presented in [2] and [3].

- BlueScratches: Page created to show the images used for testing of the blue scratch detection and removal algorithms presented in [3].

- DataFusionScratches: Page created to show the images used for testing of the scratch detection and removal algorithm presented in [4].

Publications on Digital Film Restoration

[5] Un algoritmo per salvare le "pizze" (Italian), Focus su Oggetti smarriti (e ritrovati), Almanacco della Scienza del CNR, N. 9, September 2019.

[4] L. Maddalena, A. Petrosino, G. Laccetti, A Fusion-based Approach to Digital Movie Restoration, Pattern Recognition, DOI 10.1016/j.patcog.2008.10.026, Vol. 42, no. 7, pp. 1485-1495, 2009. [Impact Factor: 3.279]

[3] L. Maddalena, A. Petrosino, Restoration of Blue Scratches in Digital Image Sequences, Image and Vision Computing, Vol. 26, Elsevier, The Netherlands, pp. 13141326, 2008. [Impact Factor: 1.496]

[2] L. Maddalena, A. Petrosino, A Comparison of Algorithms for Blue Scratch Removal in Digital Images, in A. Rizzi (Ed.), Colore e colorimetria: contributi multidisciplinari, vol. II, SIOF, ISBN-10 88-7957-252-0, pp. 133-144, 2006.

[1] L. Maddalena, Efficient Methods for Scratch Removal in Image Sequences, in Proceedings of 11th International Conference on Image Analysis and Processing (ICIAP2001), IEEE Computer Society, ISBN 0-7695-1183-X, DOI 10.1109/ICIAP.2001.957067, pp 547-552, 2001.

Last update: September 26th, 2020