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
Fast B-spline Transforms for Continuous Image Representation and Interpolation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Restoration of lost samples in digital signals
Restoration of lost samples in digital signals
A nonlinear filter for film restoration and other problems in image processing
CVGIP: Graphical Models and Image Processing
Use of the Hough transformation to detect lines and curves in pictures
Communications of the ACM
Deterioration detection for digital film restoration
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
A New Auto-Regressive (AR) Model-Based Algorithm for Motion Picture Restoration
ICASSP '97 Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97) -Volume 4 - Volume 4
Finding Edges and Lines in Images
Finding Edges and Lines in Images
Scratch detection supported by coherency analysis of motion vector fields
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Removing line scratches in digital image sequences by fusion techniques
ICIAP'05 Proceedings of the 13th international conference on Image Analysis and Processing
Adaptive line scratch detection in degraded films
Proceedings of the 9th European Conference on Visual Media Production
Accurate spatio-temporal reconstruction of missing data in dynamic scenes
Pattern Recognition Letters
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A suitable detection and reconstruction approach is proposed for removing line scratches from degraded motion picture films. The detection procedure consists of two steps. First, a simple 1D-extrema detector provides line scratch candidates. Unlike impulsive distortions, which appear randomly in an image, line artifacts persist across several frames. Furthermore, the detection process is complicated by the fact that lines occur as a natural part in interesting scenes. Therefore, we add a validation step for separating possible line defects from false detections. It consists in tracking the potential line artifacts over the frames using a Kalman filter. A new Bayesian restoration technique, dealing with both low and high frequencies around and inside the detected deteriorations, is investigated to achieve a nearly invisible reconstruction of damaged areas.