Segmentation-assisted detection of dirt impairments in archived film sequences

Ren, Jinchang and Vlachos, T. (2007) Segmentation-assisted detection of dirt impairments in archived film sequences. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 37 (2). pp. 463-470. (https://doi.org/10.1109/TSMCB.2006.886169)

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Abstract

A novel segmentation-assisted method for film dirt detection is proposed. We exploit the fact that film dirt manifests in the spatial domain as a cluster of connected pixels whose intensity differs substantially from that of its neighborhood and we employ a segmentation-based approach to identify this type of structure. A key feature of our approach is the computation of a measure of confidence attached to detected dirt regions which can be utilized for performance fine tuning. Another important feature of our algorithm is the avoidance of the computational complexity associated with motion estimation. Our experimental framework benefits from the availability of manually derived as well as objective ground truth data obtained using infrared scanning. Our results demonstrate that the proposed method compares favorably with standard spatial, temporal and multistage median filtering approaches and provides efficient and robust detection for a wide variety of test material.

ORCID iDs

Ren, Jinchang ORCID logoORCID: https://orcid.org/0000-0001-6116-3194 and Vlachos, T.;
CORE (COnnecting REpositories)