Alasdair Newson

Towards fast, generic video inpainting

Achieving globally coherent video inpainting results in reasonable time and in an automated manner is still an open problem. In this paper, we build on the seminal work by Wexler et al. to propose an automatic video inpainting algorithm yielding convincing results in greatly reduced computational times. We extend the PatchMatch algorithm to the spatio-temporal case in order to accelerate the search for approximate nearest neighbours in the patch space. We also provide a simple and fast solution to the well known over-smoothing problem resulting from the averaging of patches. Furthermore, we show that results similar to those of a supervised state-of-the-art method may be obtained on high resolution videos without any manual intervention. Our results indicate that globally coherent patch-based algorithms are feasible and an attractive solution to the difficult problem of video inpainting.

Adaptive line scratch detection in degraded films

In this paper, a robust, automatic and pixel-precision spatial line scratch detection algorithm is proposed. This algorithm deals with still images and may be followed by a temporal analysis to improve detection performances. By relaxing some of the hypotheses used in previous algorithms, detection of a wider range of scratch types is possible. The algorithms robustness and lack of external parameters is ensured by the combined use of an a contrario methodology and local statistical estimation. In this manner, over-detection in textured or cluttered areas is greatly reduced. Experiments demonstrate the algorithms ability to deal with difficult situations, in particular in the presence of noise, texture and slanted or partial scratches. Comparisons show the algorithms advantages over previous work.

Robust Automatic Line Scratch Detection in Films

Line scratch detection in old films is a particularly challenging problem due to the variable spatiotemporal characteristics of this defect. Some of the main problems include sensitivity to noise and texture, and false detections due to thin vertical structures belonging to the scene. We propose a robust and automatic algorithm for frame-by-frame line scratch detection in old films, as well as a temporal algorithm for the filtering of false detections. In the frame-by-frame algorithm, we relax some of the hypotheses used in previous algorithms in order to detect a wider variety of scratches. This steps robustness and lack of external parameters is ensured by the combined use of an a contrario methodology and local statistical estimation. In this manner, over-detection in textured or cluttered areas is greatly reduced. The temporal filtering algorithm eliminates false detections due to thin vertical structures by exploiting the coherence of their motion with that of the underlying scene. Experiments demonstrate the ability of the resulting detection procedure to deal with difficult situations, in particular in the presence of noise, texture, and slanted or partial scratches. Comparisons show significant advantages over previous work.

Temporal filtering of line scratch detections in degraded films

The film defect known as the line scratch is difficult to restore automatically due to the large number of false alarms present in scratch detection algorithms. In this paper, an algorithm for dealing with these false alarms is proposed. Validating true scratches, which is the approach generally proposed in the literature, is a difficult task since scratch characteristics are hard to determine, making tracking these defects problematic. Instead, we eliminate false alarms by analysing their compatibility with a global motion estimation. We compare our algorithm with two other scratch detection methods from the literature. Experiments show that our algorithm outperforms these two, and that the proposed temporal filtering greatly improves precision while maintaining high recall.

Non-Local Patch-Based Image Inpainting

Image inpainting is the process of filling in missing regions in an image in a plausible way. In this contribution, we propose and describe an implementation of a patch-based image inpainting algorithm. The method is actually a two-dimensional version of our video inpainting algorithm proposed in [16]. The algorithm attempts to minimise a highly non-convex functional, first introducted by Wexler et al. in [18]. The functional specifies that a good solution to the inpainting problem should be an image where each patch is very similar to its nearest neighbour in the unoccluded area. Iterations are performed in a multi-scale framework which yields globally coherent results. In this manner two of the major goals of image inpainting, the correct reconstruction of textures and structures, are addressed. We address a series of important practical issues which arise when using such an approach. In particular, we reduce execution times by using the PatchMatch [3] algorithm for nearest neighbour searches, and we propose a modified patch distance which improves the comparison of textured patches. We address the crucial issue of initialisation and the choice of the number of pyramid levels, two points which are rarely discussed in such approaches. We provide several examples which illustrate the advantages of our algorithm, and compare our results with those of state-of-the-art methods.