Real-time image recovery using temporal image fusion

In computer vision systems an unpredictable image corruption can have significant impact on its usability. Image recovery methods for partial image damage, in particular in moving scenarios, can be crucial for recovering corrupted images. In these situations, image fusion techniques can be successfully applied to congregate information taken at different instants and from different points-of-view to recover damaged parts. In this article we propose a technique for temporal and spatial image fusion, based on fuzzy classification, which allows partial image recovery upon unexpected defects without user intervention. The method uses image alignment techniques and duplicated information from previous images to create fuzzy confidence maps. These maps are then used to detect damaged pixels and recover them using information from previous frames.