Search results for "Image Restoration"

showing 10 items of 53 documents

A knowledge based architecture for the virtual restoration of ancient photos

2017

Abstract Historical images are essential documents of the recent past. Nevertheless, time and bad preservation corrupt their physical supports. Digitization can be the solution to extend their “lives”, and digital techniques can be used to recover lost information. This task is often difficult and time-consuming, if commercial restoration tools are used for the purpose. A new solution is proposed to help non-expert users in restoring their damaged photos. First, we defined a dual taxonomy for the defects in printed and digitized photos. We represented our restoration domain with an ontology and we created some rules to suggest actions to perform in case of some specific events. Classes and …

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniComputer sciencebusiness.industryProcess (engineering)Interface (Java)020206 networking & telecommunications02 engineering and technologyOntology (information science)Task (project management)Domain (software engineering)World Wide WebImage restoration Historical photos Digitization Ontology Knowledge baseKnowledge baseArtificial IntelligenceSignal Processing0202 electrical engineering electronic engineering information engineeringWeb application020201 artificial intelligence & image processingComputer Vision and Pattern RecognitionbusinessImage restoration Historical photos Digitization Ontology Knowledge baseSoftwareDigitizationPattern Recognition
researchProduct

Variational multiframe restoration of images degraded by noisy (stochastic) blur kernels

2013

This article introduces and explores a class of degradation models in which an image is blurred by a noisy (stochastic) point spread function (PSF). The aim is to restore a sharper and cleaner image from the degraded one. Due to the highly ill-posed nature of the problem, we propose to recover the image given a sequence of several observed degraded images or multiframes. Thus we adopt the idea of the multiframe approach introduced for image super-resolution, which reduces distortions appearing in the degraded images. Moreover, we formulate variational minimization problems with the robust (local or nonlocal) L^1 edge-preserving regularizing energy functionals, unlike prior works dealing wit…

Point spread functionSequenceMathematical optimizationApplied MathematicsComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION010103 numerical & computational mathematics02 engineering and technology01 natural sciencesImage (mathematics)Computational MathematicsComputer Science::Computer Vision and Pattern Recognition0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingSegmentationMinification0101 mathematicsAlgorithmEnergy (signal processing)Image restorationDegradation (telecommunications)MathematicsJournal of Computational and Applied Mathematics
researchProduct

A note on the Bregmanized Total Variation and dual forms

2009

This paper considers two approaches to perform image restoration while preserving the contrast. The first one is the Total Variation-based Bregman iterations while the second consists in the minimization of an energy that involves robust edge preserving regularization. We show that these two approaches can be derived form a common framework. This allows us to deduce new properties and to extend and generalize these two previous approaches.

Mathematical optimizationNoise measurementIterative methodCommon frameworkMinificationTotal variation denoisingAlgorithmRegularization (mathematics)Image restorationMathematics2009 16th IEEE International Conference on Image Processing (ICIP)
researchProduct

A Nonlinear Primal-Dual Method for Total Variation-Based Image Restoration

1999

We present a new method for solving total variation (TV) minimization problems in image restoration. The main idea is to remove some of the singularity caused by the nondifferentiability of the quantity $|\nabla u|$ in the definition of the TV-norm before we apply a linearization technique such as Newton's method. This is accomplished by introducing an additional variable for the flux quantity appearing in the gradient of the objective function, which can be interpreted as the normal vector to the level sets of the image u. Our method can be viewed as a primal-dual method as proposed by Conn and Overton [ A Primal-Dual Interior Point Method for Minimizing a Sum of Euclidean Norms, preprint,…

Line searchApplied MathematicsMathematical analysisTikhonov regularizationComputational Mathematicssymbols.namesakeRate of convergenceLinearizationConjugate gradient methodsymbolsNewton's methodImage restorationInterior point methodMathematicsSIAM Journal on Scientific Computing
researchProduct

A general framework for a class of non-linear approximations with applications to image restoration

2018

Este artículo se encuentra disponible en la página web de la revista en la siguiente URL: https://www.sciencedirect.com/science/article/abs/pii/S0377042717301188 Este es el pre-print del siguiente artículo: Candela, V., Falcó, A. & Romero, PD. (2018). A general framework for a class of non-linear approximations with applications to image restoration. Journal of Computational and Applied Mathematics, vol. 330 (mar.), pp. 982-994, que se ha publicado de forma definitiva en https://doi.org/10.1016/j.cam.2017.03.008 This is the pre-peer reviewed version of the following article: Candela, V., Falcó, A. & Romero, PD. (2018). A general framework for a class of non-linear approximations with applic…

Mathematical optimization010103 numerical & computational mathematics01 natural sciencesProjection (linear algebra)ConvexityImage (mathematics)symbols.namesakeProgramming (Mathematics) in Works of art.Convergence (routing)Applied mathematics0101 mathematicsProgramación (Matemáticas) - Aplicaciones en Obras de arte.Art - Conservation and restoration.Image restorationMathematicsApplied MathematicsHilbert space.Hilbert spaceAlgoritmos computacionales.Hilbert Espacio de.Linear subspaceComputer algorithms.010101 applied mathematicsComputational MathematicsObras de arte - Restauración.symbolsDeconvolutionObras de arte - Conservación.Journal of Computational and Applied Mathematics
researchProduct

Regularization Method in Infrared Image Processing

2003

Abstract Infrared images often present distortions induced by the measurement system. Thus, image processing is a vital part of infrared measurements. A distortion model based on a convolution product is presented. Image restoration is an ill-posed problem and its solution can be obtained using regularization methods. In this paper, image restoration is performed using a variation of Tikhonov regularization that makes use of the particular form of the convolution kernel matrix, which is built as a block-circulant matrix that admits a diagonal form in the two-dimensional Fourier space. The restoration procedure is used to restore a knife-edge infrared source image.

Tikhonov regularizationKernel (image processing)Diagonal formbusiness.industrySystem of measurementFrequency domainImage processingComputer visionArtificial intelligencebusinessRegularization (mathematics)Image restorationMathematicsIFAC Proceedings Volumes
researchProduct

Multidirectional Scratch Detection and Restoration in Digitized Old Images

2010

Line scratches are common defects in old archived videos, but similar imperfections may occur in printed images, in most cases by reason of improper handling or inaccurate preservation of the support. Once an image is digitized, its defects become part of that image. Many state-of-the-art papers deal with long, thin, vertical lines in old movie frames, by exploiting both spatial and temporal information. In this paper we aim to face with a more challenging and general problem: the analysis of line scratches in still images, regardless of their orientation, color, and shape. We present a detection/restoration method to process this defect.

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniComputer sciencebusiness.industryOrientation (computer vision)lcsh:ElectronicsProcess (computing)ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONlcsh:TK7800-8360Image processingImage processing Scratch detectionImage restorationScratchFace (geometry)Signal ProcessingPattern recognition (psychology)Line (geometry)Computer visionArtificial intelligenceElectrical and Electronic EngineeringbusinesscomputerImage restorationInformation Systemscomputer.programming_languageImage restoration; Image processing Scratch detectionEURASIP Journal on Image and Video Processing
researchProduct

Patch-Based Image Denoising Model for Mixed Gaussian Impulse Noise Using L1 Norm

2017

Image denoising is the classes of technique used to free the image form the noise. The noise in the image may be added during the observation process due to the improper setting of the camera lance, low-resolution camera, cheap, and low-quality sensors, etc. Noise in the image may also be added during the image restoration, image transmission through the transmission media. To obtain required information from image, image must be noise free, i.e., high-frequency details must be present in the image. There are number of applications where image denoising is needed such as remote location detection, computer vision, computer graphics, video surveillance, etc. In last two decades, numbers of m…

Mathematical optimizationbusiness.industryComputer scienceGaussianComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONTransmission mediumImpulse (physics)Non-local meansImpulse noiseComputer graphicssymbols.namesakeGaussian noiseComputer Science::Computer Vision and Pattern RecognitionsymbolsComputer visionArtificial intelligencebusinessImage restoration
researchProduct

Restoration and Enhancement of Historical Stereo Photos Through Optical Flow

2021

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. 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 …

Computer sciencemedia_common.quotation_subjectNoise reductionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONOptical flow02 engineering and technologyConsistency (database systems)Image restoration0202 electrical engineering electronic engineering information engineeringRedundancy (engineering)Contrast (vision)Computer visionImage restorationmedia_commonSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniSettore INF/01 - Informaticabusiness.industryOptical flow021001 nanoscience & nanotechnologySensor fusionStereo matchingTransmission (telecommunications)Image denoisingImage enhancementGradient filtering020201 artificial intelligence & image processingArtificial intelligence0210 nano-technologybusiness
researchProduct

Optical calibration of a multispectral imaging system based on interference filters

2005

We present a new approach to optically calibrate a multispectral imaging system based on interference filters. Such a system typically suffers from some blurring of its channel images. Because the effectiveness of spectrum reconstruction depends heavily on the quality of the acquired channel images, and because this blurring negatively affects them, a method for deblurring and denoising them is required. The blur is modeled as a uniform intensity distribution within a circular disk. It allows us to characterize, quantitatively, the degradation for each channel image. In terms of global reduction of the blur, it consists of the choice of the best channel for the focus adjustment according to…

DeblurringComputer sciencebusiness.industryNoise reductionWiener filterMultispectral imageComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONGeneral EngineeringImage processingReal imageAtomic and Molecular Physics and OpticsMultispectral pattern recognitionsymbols.namesakeComputer Science::GraphicsInterference (communication)Computer Science::Computer Vision and Pattern RecognitionsymbolsComputer visionArtificial intelligenceOptical filterFocus (optics)businessImage restorationOptical Engineering
researchProduct