Performance of Wavelet-based Multiresolution Motion Estimation for Inbetweeningin Old Animated Films

This  paper  investigates the  performance  of  wavelet-based multiresolution  motion  estimation (MRME)  for  inbetweening  in  old  animated films  using  three different  MRME  schemes.  The  three  schemes  are:  coarse-to fine with a wavelet-based MRME, one of Zhang's MRMEs, and an MRME in the spatial domain.  In order to make a performance comparison of these MRME  schemes,  two  video  sequences were  used  for  a  simulation.  The  experimental results  show  that  the  coarse-to-fine  method  performed  better  than  Zhang's  MRME  and  the  MRME in the spatial domain. The evaluation results  on block size 9x9 indicate that the coarse-to-fine method had an average peak signal-to-noise ratio (PSNR) of  23.48 dB for the first sequence and 29.84 for the second sequence

A Dynamic Programming Solution to Bounded Dejittering Problems

We propose a dynamic programming solution to image dejittering problems with bounded displacements and obtain efficient algorithms for the removal of line jitter, line pixel jitter, and pixel jitter.Comment: The final publication is available at link.springer.co

FastDVDnet: Towards Real-Time Video Denoising Without Explicit Motion Estimation

In this paper, we propose a state-of-the-art video denoising algorithm based on a convolutional neural network architecture. Until recently, video denoising with neural networks had been a largely under explored domain, and existing methods could not compete with the performance of the best patch-based methods. The approach we introduce in this paper, called FastDVDnet, shows similar or better performance than other state-of-the-art competitors with significantly lower computing times. In contrast to other existing neural network denoisers, our algorithm exhibits several desirable properties such as fast run-times, and the ability to handle a wide range of noise levels with a single network model. The characteristics of its architecture make it possible to avoid using a costly motion compensation stage while achieving excellent performance. The combination between its denoising performance and lower computational load makes this algorithm attractive for practical denoising applications. We compare our method with different state-of-art algorithms, both visually and with respect to objective quality metrics

Restoration and enhancement of historical stereo photos

Restoration of digital visual media acquired from repositories of historical photographic and cinematographic material is of key importance for the preservation, study and transmission of the legacy of past cultures to the coming generations. In this paper, a fully automatic approach to the digital restoration of historical stereo photographs is proposed, referred to as Stacked Median Restoration plus (SMR+). The approach exploits the content redundancy in stereo pairs for detecting and fixing scratches, dust, dirt spots and many other defects in the original images, as well as improving contrast and illumination. This is done by estimating the optical flow between the images, and using it to register one view onto the other both geometrically and photometrically. Restoration is then accomplished in three steps: (1) image fusion according to the stacked median operator, (2) low-resolution detail enhancement by guided supersampling, and (3) iterative visual consistency checking and refinement. Each step implements an original algorithm specifically designed for this work. The restored image is fully consistent with the original content, thus improving over the methods based on image hallucination. Comparative results on three different datasets of historical stereograms show the effectiveness of the proposed approach, and its superiority over single-image denoising and super-resolution methods. Results also show that the performance of the state-of-the-art single-image deep restoration network Bringing Old Photo Back to Life (BOPBtL) can be strongly improved when the input image is pre-processed by SMR+

Noise, artifact and the uncanny in large scale digital photographic practice.

This dissertation explores the question: why, when encountering the products of many new technologies delivering information via a new media, do I often experience a feeling of disquiet or estrangement? I use the example of laser-photographic printing to explore the issue through a program of practice-based research. The outcome of this line of enquiry includes an original contribution via three series of large-format digital photographic works: Presenting "The Amazing Kriels", Home At Last, and Pure. In this thesis, which supports the main body of the research, that is, the practice-based research, I will briefly review the case for artefact as noise within photographic printing, articulate a significant difference between the artefact levels of traditional analogue and Lambda prints, present original dialogical evidence for estrangement in the latter, and identify it via readings of Sigmund Freud's "The Uncanny" and McLuhan's "The Gadget Lover", as a function of the uncanny. I will propose an original rewriting of McLuhan's ideas of "hot" and "cool" media, as well as the cycles of irritation/mediation repression within McLuhan's media theory as a direction for future research, and relate them to a shift from large-scale analogue photographic printing to Lambda printing