Abstract
A detection and tracking approach is proposed for line scratch removal in a digital film restoration process. Unlike random impulsive distortions such as dirt spots, line scratch artifacts persist across several frames. Hence, motion compensated methods will fail, as well as single-frame methods if scratches are unsteady or fragmented.
The proposed method uses as input projections of each image of the input sequence. First, a 1D-extrema detector provides candidates. Next, a MHT (Multiple Hypothesis Tracker) uses these candidates to create and keep multiple hypothesis. As the tracking goes further through the sequence, each hypothesis gains or looses evidence. To avoid a combinatorial explosion, the hypothesis tree is sequentially pruned, preserving a list of the best ones. An energy function (quality of the candidates, comparison to a model) is used for the path hypothesis sorting. As hypothesis are set up at each iteration, even if no information is available, a tracked path might cross gaps (missed detection or speckled scratches).
At last, the tracking stage feeds the correction process. Since this contribution focus on the detection stage, only tracking results are given.
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Besserer, B., Thiré, C. (2004). Detection and Tracking Scheme for Line Scratch Removal in an Image Sequence. In: Pajdla, T., Matas, J. (eds) Computer Vision - ECCV 2004. ECCV 2004. Lecture Notes in Computer Science, vol 3023. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24672-5_21
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DOI: https://doi.org/10.1007/978-3-540-24672-5_21
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