image restoration-32




Image restoration of damaged or Erased Manuscripts
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KT Knox, RL Easton Jr ,European Signal , 2008 ,eurasip.org
ABSTRACT Modern imaging techniques have been applied to ancient manuscripts to
recover writings that are not visible to the naked eye. Over the years, many of these
manuscripts have been damaged by the elements or even intentionally erased and re-

Image restoration via nonlocal Mumford-Shah regularizers
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M Jung ,UCLA CAM Report, 2009 ,arachne.math.ucla.edu
Abstract. We wish to recover an image corrupted by blur and Gaussian or impulse noise in a
variational framework. We use two data-fidelity terms depending on the type of noise, and
several local and nonlocal regularizers. Inspired by Buades, Coll, Morel and Gilboa-Osher

Image restoration and simultaneous edge detection by optimal control methods
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L Franek, M Franek, H Maurer ,Opt. Contr. Appl. , 2011 ,3dsp.uni-muenster.de
Abstract. The present paper is concerned with the numerical solution of multidimensional
control problems of Dieudonné-Rashevsky type by discretization methods and large-scale
optimization techniques. We prove first a convergence theorem wherein the difference of 

Iterative regularization and nonlinear inverse scale space methods in image restoration
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Due to its increasing applications, digital image processing has become a more and more
important and active research field in the past decade. For a recent review of image
denoising algorithms please refer to

An EfficientMRF Image-Restoration Technique Using Deterministic Scale-Based Optimization
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AN IMAGE ,LINCOLN LABORATORY JOURNAL, 1993 ,ll.mit.edu
Background In this section the Bayesian formulation of image restoration is reviewed to
show the formal connections to the restoration method that is the subject of this article. The
Bayesian formulation relates the posterior probability that an estimate of the true image xr 

Noise image restoration by spatial filters
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L Hargaš, M Hrianka ,Radioelektronika 2003: 13th international ,urel.feec.vutbr.cz
Image restoration methods are used to improve the appearance of an image by appli- cation
of a restoration process that uses a mathematical model for image degradation. Examples of
the types of degradation include: ,geometric distortion caused by imperfect lenses,

Iterative blind image restoration using local constraints
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K May, T Stathaki , Conference on Signal , 1998 ,ivpl.ece.northwestern.edu
ABSTRACT A new method of incorporating local image constraints into blind image
restoration is proposed. The local mean and variance of the degraded image are used to
obtain an initial estimate of the pixel intensity bounds. As the restoration proceeds, the 

Fast and automated wavelet-regularized image restoration in fluorescence microscopy
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C Vonesch ,2009 ,biblion.epfl.ch
Abstract The subject of this thesis is image restoration, that is, deconvolution and denoising.
Our work is motivated by applications in the rapidly expanding field of biological imaging
and in particular fluorescence microscopy. Inverse problems in this area typically involve 

Edge-preserving regularization in image restoration
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CAZ Barcelos ,to appear Boletim (SBMAC), 2002 ,sbmac.org.br
Abstract The reconstruction of an image u (x, y) that describes a real scene from
experimental data (observed image) I (x, y) can be identified as an inverse problem. This
problem is generally ill-posed in the sense of Hadamard. The regularization of an inverse 

GIS image compression and restoration: A neural network approach
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YAL Al-Bastaki ,Information Technology Journal, 2006 ,198.170.104.138
Abstract: Resolution of images for Geographical Information System (GIS) was usually
desired to be as high as possible. The higher resolution of the image is larger its data size.
The large data size of a high resolution image brings difficulties in dealing with it. 

Improving microarray spots segmentation by k-means driven adaptive image restoration
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A Daskalakis, D Cavouras ,Proceedings of the , 2006 ,medlab.cc.uoi.gr
Abstract—Complementary DNA microarray experiments are used to study human genome.
However, microarray images are corrupted by spatially inhomogeneous noise that
deteriorates image and consequently gene expression. An adaptive microarray image

Primal dual algorithms for convex models and applications to image restoration, registration and nonlocal inpainting
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JE Esser ,2010 ,math.ucla.edu
An important class of problems in image processing, and now also compressive sensing, is
convex programs involving l1 or total variation (TV) minimization. The use of l1 and TV
regularizers has been shown to be very effective in regularizing inverse problems where 

Sparse Bayesian image restoration
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Conference on Image , 2010 ,decsai.ugr.es
ABSTRACT In this paper we propose a novel Bayesian algorithm for image restoration and
parameter estimation. We utilize an image prior where Gaussian distributions are placed per
pixel in the high-pass filter outputs of the image. By following the hierarchical Bayesian 

Comparison of image restoration methods for bioluminescence imaging
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S Akkoul, R Ledee, R Leconge, C Leger  Image and Signal , 2008 ,Springer
Bioluminescence imaging is a recent modality to visualize biological effects, especially for
small animals. However, the acquired images are degraded by diffusion and absorption
phenomena from the tissue and by the acquisition system itself. In this paper, we use 

Image De-Noising and Restoration Using Wavelet Transform
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A Procházka, J Ptácek ,International European Control , 2004 ,nt.ntnu.no
Abstract Image de-noising and restoration represent basic problems in image processing
with many different applications including engineering, reconstruction of missing data during
their transmission and enhancement of biomedical structures as well. This problem occurs 

Mosaicing and restoration from blurred image sequence taken with moving camera
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M Onogi ,Pattern Recognition and Image Analysis, 2005 ,Springer
A wide-area image can be synthesized from an image sequence taken with a moving
camera by using image mosaicing techniques. However, motion blur caused by the motion
of the camera may significantly degrade the quality of the synthesized image. In this paper

The restoration of camera documents through image segmentation
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S Lu ,Document Analysis Systems VII, 2006 ,Springer
This paper presents a document restoration technique that is able to flatten curled document
images captured through a digital camera. The proposed method corrects camera images of
documents through image partition, which divides distorted text lines into multiple small 

Blind image restoration by combining wavelet transform and RBF neural network
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International Journal of Wavelets , 2007 ,cs.bnu.edu.cn
In this paper, we present a novel technique for restoring a blurred noisy image without any
prior knowledge of the blurring function and the statistics of noise. The technique combines
wavelet transform with radial basis function (RBF) neural network to restore the given 

Image restoration by lifting-based wavelet domain E-median filter
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S Koç ,ETRI journal, 2006 ,etrij.etri.re.kr
In this paper, we propose a method of applying a liftingbased wavelet domain e-median filter
(LBWDEMF) for image restoration. LBWDEMF helps in reducing the number of
computations. An e-median filter is a type of modified median filter that processes each 


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