Film line scratch removal using Kalman filtering and Bayesian restoration

A suitable detection/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. Line artifacts persist across several frames. Therefore, to reject false detections, the detected scratches are tracked over the sequence using a Kalman filter. A new Bayesian restoration technique, dealing with both low and high frequencies around and inside the detected artifacts, is investigated to achieve a near invisible restoration of damaged areas.

[1]  Christopher M. Brown,et al.  Tutorial on Filtering, Restoration, and State Estimation , 1995 .

[2]  Robin D. Morris,et al.  Image Sequence Restoration Using Gibbs Distributions , 1995 .

[3]  Greg Welch,et al.  Welch & Bishop , An Introduction to the Kalman Filter 2 1 The Discrete Kalman Filter In 1960 , 1994 .

[4]  Anil C. Kokaram,et al.  Detection and removal of line scratches in degraded motion picture sequences , 1996, 1996 8th European Signal Processing Conference (EUSIPCO 1996).

[5]  Olivier Buisson,et al.  Detection and removal of line scratches in motion picture films , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).

[6]  Etienne Decenciere Ferrandiere.  Restauration automatique de films anciens , 1997 .

[7]  Laurent Joyeux.  Reconstruction de séquences d'images haute résolution : application à la restauration de films cinématographiques , 2000 .

[8]  Dilip Krishnan,et al.  A new auto-regressive (AR) model-based algorithm for motion picture restoration , 1997, 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[9]  J. Canny.  Finding Edges and Lines in Images , 1983 .

[10]  A. Kokaram.  Motion picture restoration , 1998 .

[11]  Deterioration detection for digital film restoration , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[12]  Thomas S. Huang,et al.  Image sequence analysis , 1981 .

[13]  Jorge L. C. Sanz,et al.  Radon and projection transform-based computer vision , 1988 .

[14]  Richard O. Duda,et al.  Use of the Hough transformation to detect lines and curves in pictures , 1972, CACM.

[15]  David Suter,et al.  Historical Film Restoration and Video Coding , 1996 .