Efficient Method For Scratch Lines Noise Removal From Video

The digitalization and transfer of older films into high definition (HD) formats imply that high quality of restoration is necessary. Now a day�s Digital film restoration is an area under discussion of increasing interest to researchers and film archives alike. Old films, including cultural heritage masterpieces, are being digitally premastered and transferred into novel, higher quality formats and distributed through various means such as DVD, Blu-ray or HD pictures. Detection of Line scratches in old movies is a particularly difficult problem due to the variable spatiotemporal characteristics of this deficiency. Some of the main problems consist of sensitivity to noise and texture, and false detections due to thin vertical structures belonging to the scene. Automatic finding of image damaged regions is the key to automatic video image in-painting. Vertical scratches are the common damages in the old film. As the film is a collection of number of frames arrayed together to produce a motion sequence hence it becomes a lengthy and tedious work to process any video format in any manner. Normally if any scratch or noise generated on films it remains as it is on many frames in sequence in film which can be benefitted by the removal process by initially checking noise area on earlier slide. Hence proposed system is aimed at designing and developing of line scratches detection from old films and remove it. A line scratches detection algorithm based on edge detection is proposed. Edge detection is nothing but an image processing technique for finding the boundaries of objects inside images. The proposed algorithm first uses the operator which has the largest response to the vertical edge in Sobel operator to detect edges, and then uses canny operator to detect edges further. Third, we detect vertical lines in the image through probabilistic Hough transform. Finally, we obtain the true locations of the vertical lines scratches through morphology and width constraints. We contribute for removal of scratches using a new nonlinear continued fraction method dealing with both spatial and temporal information around the scratch is investigated in the restoration stage

Detection and Removal of Long Scratch Lines in Aged Films

[[abstract]]Historical films usually have defects. We study the type of defects, and propose a series of solutions to detect defects before they are repaired by our inpainting algorithms. This paper focuses on a difficult issue to locate long vertical line defects in aged films. A progressive detection algorithm is proposed. We are able to detect more than 86% (recall rate) of effective line defects. These line defects are then removed step by step. The experiments use real historical video collected from national museum and public channel, instead of using computer generated noise. The results are visually pleasant based on our subjective evaluation by volunteers[[conferencetype]]國際[[conferencedate]]20060709~20060712[[iscallforpapers]]Y[[conferencelocation]]Toronto, Ont., Canad

Sur la Restauration et l'Edition de Vidéo : Détection de Rayures et Inpainting de Scènes Complexes

The inevitable degradation of visual content such as images and films leads to the goal ofimage and video restoration. In this thesis, we look at two specific restoration problems : the detection ofline scratches in old films and the automatic completion of videos, or video inpainting as it is also known.Line scratches are caused when the film physically rubs against a mechanical part. This origin resultsin the specific characteristics of the defect, such as verticality and temporal persistence. We propose adetection algorithm based on the statistical approach known as a contrario methods. We also proposea temporal filtering step to remove false alarms present in the first detection step. Comparisons withprevious work show improved recall and precision, and robustness with respect to the presence of noiseand clutter in the film.The second part of the thesis concerns video inpainting. We propose an algorithm based on theminimisation of a patch-based functional of the video content. In this framework, we address the followingproblems : extremely high execution times, the correct handling of textures in the video and inpaintingwith moving cameras. We also address some convergence issues in a very simplified inpainting context.La degradation inévitable des contenus visuels (images, films) conduit nécessairementà la tâche de la restauration des images et des vidéos. Dans cetre thèse, nous nous intéresserons àdeux sous-problèmes de restauration : la détection des rayures dans les vieux films, et le remplissageautomatique des vidéos (“inpainting vidéo en anglais).En général, les rayures sont dues aux frottements de la pellicule du film avec un objet lors de laprojection du film. Les origines physiques de ce défaut lui donnent des caractéristiques très particuliers.Les rayures sont des lignes plus ou moins verticales qui peuvent être blanches ou noires (ou parfois encouleur) et qui sont temporellement persistantes, c’est-à-dire qu’elles ont une position qui est continuedans le temps. Afin de détecter ces défauts, nous proposons d’abord un algorithme de détection basésur un ensemble d’approches statistiques appelées les méthodes a contrario. Cet algorithme fournitune détection précise et robuste aux bruits et aux textures présentes dans l’image. Nous proposonségalement une étape de filtrage temporel afin d’écarter les fausses alarmes de la première étape dedétection. Celle-ci améliore la précision de l’algorithme en analysant le mouvement des détections spatiales.L’ensemble de l’algorithme (détection spatiale et filtrage temporel) est comparé à des approchesde la littérature et montre un rappel et une précision grandement améliorés.La deuxième partie de cette thèse est consacrée à l’inpainting vidéo. Le but ici est de remplirune région d’une vidéo avec un contenu qui semble visuellement cohérent et convaincant. Il existeune pléthore de méthodes qui traite ce problème dans le cas des images. La littérature dans le casdes vidéos est plus restreinte, notamment car le temps d’exécution représente un véritable obstacle.Nous proposons un algorithme d’inpainting vidéo qui vise l’optimisation d’une fonctionnelle d’énergiequi intègre la notion de patchs, c’est-à-dire des petits cubes de contenu vidéo. Nous traitons d’abord leprobl’‘eme du temps d’exécution avant d’attaquer celui de l’inpainting satisfaisant des textures dans lesvidéos. Nous traitons également le cas des vidéos dont le fond est en mouvement ou qui ont été prisesavec des caméras en mouvement. Enfin, nous nous intéressons à certaines questions de convergencede l’algorithme dans des cas très simplifiés

A study of motion-based detection and removal of defects in digital motion pictures

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1995.Includes bibliographical references (leaves 87-88).by Carl H. Taniguchi.M.S

Video inpainting for non-repetitive motion

Master'sMASTER OF SCIENC

Intelligent Transportation Related Complex Systems and Sensors

Building around innovative services related to different modes of transport and traffic management, intelligent transport systems (ITS) are being widely adopted worldwide to improve the efficiency and safety of the transportation system. They enable users to be better informed and make safer, more coordinated, and smarter decisions on the use of transport networks. Current ITSs are complex systems, made up of several components/sub-systems characterized by time-dependent interactions among themselves. Some examples of these transportation-related complex systems include: road traffic sensors, autonomous/automated cars, smart cities, smart sensors, virtual sensors, traffic control systems, smart roads, logistics systems, smart mobility systems, and many others that are emerging from niche areas. The efficient operation of these complex systems requires: i) efficient solutions to the issues of sensors/actuators used to capture and control the physical parameters of these systems, as well as the quality of data collected from these systems; ii) tackling complexities using simulations and analytical modelling techniques; and iii) applying optimization techniques to improve the performance of these systems. It includes twenty-four papers, which cover scientific concepts, frameworks, architectures and various other ideas on analytics, trends and applications of transportation-related data

RIACS

The Research Institute for Advanced Computer Science (RIACS) was established by the Universities Space Research Association (USRA) at the NASA Ames Research Center (ARC) on June 6, 1983. RIACS is privately operated by USRA, a consortium of universities that serves as a bridge between NASA and the academic community. Under a five-year co-operative agreement with NASA, research at RIACS is focused on areas that are strategically enabling to the Ames Research Center's role as NASA's Center of Excellence for Information Technology. The primary mission of RIACS is charted to carry out research and development in computer science. This work is devoted in the main to tasks that are strategically enabling with respect to NASA's bold mission in space exploration and aeronautics. There are three foci for this work: (1) Automated Reasoning. (2) Human-Centered Computing. and (3) High Performance Computing and Networking. RIACS has the additional goal of broadening the base of researcher in these areas of importance to the nation's space and aeronautics enterprises. Through its visiting scientist program, RIACS facilitates the participation of university-based researchers, including both faculty and students, in the research activities of NASA and RIACS. RIACS researchers work in close collaboration with NASA computer scientists on projects such as the Remote Agent Experiment on Deep Space One mission, and Super-Resolution Surface Modeling