A New Class of Detail-Preserving Filters for Image Processing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Radon and projection transform-based computer vision: algorithms, a pipeline architecture, and industrial applications
Restoration of lost samples in digital signals
Restoration of lost samples in digital signals
Robust incremental optical flow
Robust incremental optical flow
Motion Picture Restoration: Digital Algorithms for Artefact Suppression in Degraded Motion Picture Film and Video
A Pyramid Framework for Early Vision: Multiresolutional Computer Vision
A Pyramid Framework for Early Vision: Multiresolutional Computer Vision
Hierarchical Model-Based Motion Estimation
ECCV '92 Proceedings of the Second European Conference on Computer Vision
Deterioration detection for digital film restoration
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Optic flow calculation using robust statistics
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Relaxing the Brightness Constancy Assumption in Computing Optical Flow
Relaxing the Brightness Constancy Assumption in Computing Optical Flow
Simultaneous recursive displacement estimation and restoration of noisy-blurred image sequences
IEEE Transactions on Image Processing
Detection of motion-incoherent components in video streams
IEEE Transactions on Information Forensics and Security
Trainable blotch detection on high resolution archive films minimizing the human interaction
Machine Vision and Applications - Integrated Imaging and Vision Techniques for Industrial Inspection
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Motion picture films are susceptible to local degradations such as dust spots. Other deteriorations are global such as intensity and spatial jitter. It is obvious that motion needs to be compensated for before the detection/correction of such local and dynamic defects. Therefore, we propose a hierarchical motion estimation method ideally suited for high resolution film sequences. This recursive block-based motion estimator relies on an adaptive search strategy and Radon projections to improve processing speed. The localization of dust particles then becomes straightforward. Thus, it is achieved by simple inter-frame differences between the current image and motion compensated successive and preceding frames. However, the detection of spatial and intensity jitter requires a specific process taking advantage of the high temporal correlation in the image sequence. In this paper, we present our motion compensation-based algorithms for removing dust spots, spatial and intensity jitter in degraded motion pictures. Experimental results are presented showing the usefulness of our motion estimator for film restoration at reasonable computational costs.