Adaptive blotches detection for film restoration

Blotches are very common, localized, and non persistent impairments in digitized film archive. Many methods have been proposed so far for detecting them and restoring the underlying regions. Most detection techniques rely on the hypothesis that blotches contradict a model of motion regularity and, up to a prior motion compensation, correspond to significant temporal variations of intensity with respect to a global threshold. In this paper, we propose a statistical approach to detect blotches in image sequences, which yields thresholds adapted to the local statistics of the frames, and which takes into account gray level differences in neighborhoods instead of isolated points. This approach is combined with a block-based motion estimation. The whole procedure is confronted with classical approaches on several sequences.