@article{
 id = {c54ecbf6-8684-3df1-ad78-63f0a714287c},
 title = {Robust Automatic Line Scratch Detection in Films},
 type = {article},
 year = {2014},
 identifiers = {[object Object]},
 keywords = {Film restoration,a contrario methods,adaptive detection,affine motion estimation,line scratches,type/journal},
 created = {2014-01-23T09:55:09.000Z},
 pages = {1240-1254},
 volume = {23},
 websites = {http://hal.archives-ouvertes.fr/hal-00927007},
 month = {3},
 day = {10},
 accessed = {2014-02-04},
 file_attached = {false},
 profile_id = {764ad609-ab47-3f3e-acff-e0eb66664fdb},
 last_modified = {2015-01-27T17:20:37.000Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Newson2014:TIP-scratches},
 abstract = {Line scratch detection in old films is a particularly challenging problem due to the variable spatio-temporal characteristics of this defect. Some of the main problems include sensitivity to noise and texture, and false detections due to thin vertical structures belonging to the scene. We propose a robust and automatic algorithm for frame-by-frame line scratch detection in old films, as well as a temporal algorithm for the filtering of false detections. In the frame-by-frame algorithm, we relax some of the hypotheses used in previous algorithms in order to detect a wider variety of scratches. This step's robustness and lack of external parameters is ensured by the combined use of an a contrario methodology and local statistical estimation. In this manner, over-detection in textured or cluttered areas is greatly reduced. The temporal filtering algorithm eliminates false detections due to thin vertical structures by exploiting the coherence of their motion with that of the underlying scene. Experiments demonstrate the ability of the resulting detection procedure to deal with difficult situations, in particular in the presence of noise, texture and slanted or partial scratches. Comparisons show significant advantages over previous work.},
 bibtype = {article},
 author = {Newson, Alasdair and Almansa, Andres and Gousseau, Yann and Perez, Patrick},
 journal = {IEEE Transactions on Image Processing},
 number = {3}
}

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Experiments demonstrate the ability of the resulting detection procedure to deal with difficult situations, in particular in the presence of noise, texture and slanted or partial scratches. 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