Bernard Besserer

Detection and removal of line scratches in motion picture films

Line scratches are common degradations in motion picture films. This paper presents an efficient method for line scratches detection strengthened by a Kalman filter. A new interpolation technique, dealing with both low and high frequencies (i.e. film grain) around the line artifacts, is investigated to achieve a nearby invisible reconstruction of damaged areas. Our line scratches detection and removal techniques have been validated on several film sequences.

Reconstruction of degraded image sequences. Application to film restoration

Abstract A suitable detection–reconstruction approach is proposed for removing impulsive distortion and other types of deterioration from degraded image sequences. The main application that has motivated this work is the problem of digital film restoration for the movie industry, which has only very recently been explored. Line artifacts, which are prominent degradations in motion picture films, are also considered here. The detection procedure consists of two steps. First, a morphological filter provides impulsive distortions and line scratch candidates. Unlike impulsive distortions, which appear randomly in an image, line artifacts persist in nearby or the same location across several frames. Furthermore, the detection process is complicated by the fact that lines occur as 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. An interpolation technique, dealing with both low and high frequencies around the detected deteriorations, is investigated to achieve a nearly invisible reconstruction of damaged areas.

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.

Deterioration detection for digital film restoration

This paper presents a robust technique to detect local deteriorations of old cinematographic films. This method relies on spatio-temporal information and combines two different detectors: a morphological detector which uses spatial properties of deteriorations, and a dynamic detector based on motion estimation techniques. Our deterioration detector has been validated on several film sequences and turned out to be a powerful tool for digital film restoration.

Tracking and MAP Reconstruction of line scratches in degraded motion pictures

Abstract. 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.

Perceptual approach for unsupervised digital color restoration of cinematographic archives

The cinematographic archives represent an important part of our collective memory. We present in this paper some advances in automating the color fading restoration process, especially with regard to the automatic color correction technique. The proposed color correction method is based on the ACE model, an unsupervised color equalization algorithm based on a perceptual approach and inspired by some adaptation mechanisms of the human visual system, in particular lightness constancy and color constancy. There are some advantages in a perceptual approach: mainly its robustness and its local filtering properties, that lead to more effective results. The resulting technique, is not just an application of ACE on movie images, but an enhancement of ACE principles to meet the requirements in the digital film restoration field. The presented preliminary results are satisfying and promising.

Global motion estimation for MPEG-encoded streams

This paper explains a method for global motion characterization using a Hough-transform-like technique to estimate the motion parameters. Motion information provided by each picture sample is gathered in an accumulator corresponding to a parameter space, which is derived from our simple motion model. The document then focuses on the use of MPEG stream as input data, dealing with the available motion compensation information as input vectors for our system. Pros, cons and improvements are discussed.

Recent progress in automatic digital restoration of color motion pictures

The motion pictures represent a precious cultural heritage, however the chemical support on which they are recorded becomes unstable with time, unless they are stored at low temperatures. Some defects affecting color movies, such as bleaching, are out of reach of photochemical restoration means, digital restoration is hence unquestionable. We propose an original automatic technique for faded image correction. Bleaching results in damage to one or two chromatic layers, giving a drab image with poor saturation and an overall color cast. Our automatic fading correction technique consists in reviving the colors of the image (color enhancement), then in balancing the colors of the image.

Tuning of perceptual technique for digital movie color restoration

In this paper we present tests and results of an automatic color fading restoration process for digitized movies. The proposed color correction method is based on the ACE model, an unsupervised color equalization algorithm based on a perceptual approach and inspired by some mechanisms of the human visual system. This perceptual approach is local, robust and does not need any user region selection or any other user supervision. However the model has a small number of parameters that has to be set once before the filtering. The tests presented in this paper aim to study these parameters and find their effect on the final result.

Motion compensated film restoration

Abstract. 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.