image restoration-111

Grouped coordinate descent algorithms for robust edge-preserving image restoration
Proc. SPIE, 1997 ,
ABSTRACT We present a new class of algorithms for edge-preserving restoration of
piecewise-smooth images measured in non-Gaussian noise under shift-variant blur. The
algorithms are based on minimizing a regularized objective function, and are guaranteed 

Image restoration via nonstandard diffusion
S Levine, Y Chen ,Duquesne University, Department , 2004 ,
Abstract We present a functional of nonstandard growth for which the corresponding
minimization problem provides a model for image denoising, enhancement, and restoration.
The diffusion resulting from the proposed model is a combination of isotropic and 

Solving constrained total-variation image restoration and reconstruction problems via alternating direction methods
MK Ng, P Weiss ,SIAM Journal on Scientific , 2010 ,
Abstract In this paper, we study alternating direction methods for solving constrained total-
variation image restoration and reconstruction problems. Alternating direction methods can
be implementable variants of the classical augmented Lagrangian method for optimization 

Error estimation for Bregman iterations and inverse scale space methods in image restoration
M Burger, E Resmerita ,Computing, 2007 ,Springer
Summary In this paper, we consider error estimation for image restoration problems based
on generalized Bregman distances. This error estimation technique has been used to derive
convergence rates of variational regularization schemes for linear and nonlinear inverse 

A fourth order dual method for staircase reduction in texture extraction and image restorationproblems
TF Chan, S Esedoglu ,UCLA CAM Report, 2005 ,
Abstract We propose a fourth order dual method for the minimization of the non-smooth semi-
norm?· 1 when in amalgamation with new staircase reducing texture decomposition and
restoration models of image processing. The proposed models incorporating this high 

PSF estimation with applications in autofocus and image restoration
F Rooms, M Ronsse,    IEEE Signal Processing , 2002 ,
ABSTRACT In this paper, a wavelet based method is proposed to estimate the blur in an
image using information contained in the image itself. We look at the sharpness of the
sharpest edges in the blurred image, which contain information about the blurring. 

On the choice of regularisation parameter in image restoration
J Kay ,Pattern Recognition, 1988 ,Springer
This paper considers the application of the method of regularisation within the context of the
restoration of degraded two-dimensional images. In particular, several recipes for choosing
an appropriate degree of regularisation are described and their performance compared 

Degraded character image restoration
JD Hobby , on Document Analysis and Image Retrieval, 1996 ,
Abstract The design and analysis of an algorithm for the restoration of degraded images of
machine-printed characters is presented. The input is a set of degraded bilevel images of a
single unknown character; the output is an approximation to the character’s ideal artwork. 

Adaptive iterative image restoration with reduced computational load
S EFSTRATIADIS ,Optical , 1990 ,
Abstract. In this paper, methods for reducing the computational load of an adaptive iterative
image restoration algorithm while producing a re-stored image of high visual quality are
proposed. These methods are based on a class of iterative restoration algorithms that 

Image sequence restoration: a PDE based coupled method for image restoration and motion segmentation
Computer Vision—ECCV’98, 1998 ,Springer
This article deals with the problem of restoring and segmenting noisy image sequences with
a static background. Usually, motion segmentation and image restoration are tackled
separately in image sequence restoration. Moreover, segmentation is often noise 

Frequency-domain adaptive iterative image restoration and evaluation of the regularization parameter
MG Kang, AK Katsaggelos ,Optical Engineering- , 1994 ,
Abstract. An important consideration in regularized image restoration is the evaluation of the
regularization parameter. Various techniques exist in the literature for the evaluation of this
parameter, which depend on the assumed prior knowledge about the problem. These 

Iterative algorithms based on the decouple of deblurring and denoising for image restoration
Y Wen, M Ng ,SIAM Journal on Scientific Computing, 2008 ,
Abstract. In this paper, we propose iterative algorithms for solving image restoration
problems. The iterative algorithms are based on the decouple of deblurring and denoising
steps in the restoration process. In the deblurring step, an e cient deblurring method using 

Type of blur and blur parameters identification using neural network and its application to image restoration
Artificial Neural , 2002 ,Springer
The original solution of the blur and blur parameters identification problem is presented in
this paper. A neural network based on multi-valued neurons is used for the blur and blur
parameters identification. It is shown that using simple single-layered neural network it is 

A nonlinear multigrid method for total variation minimization from image restoration
K Chen ,Journal of Scientific Computing, 2007 ,Springer
Abstract Image restoration has been an active research topic and variational formulations
are particularly effective in high quality recovery. Although there exist many modelling and
theoretical results, available iterative solvers are not yet robust in solving such modeling 

Avalanche photodiode detection with object scanning and image restoration provides 2-4 fold resolution increase in two-photon fluorescence microscopy
H Kano, HTM Van Der Voort, M Schrader ,Bioimaging, 1996 ,
Abstract. High-quantum-efficiency photodetection, millisecond pixel dwell time stage
scanning and image restoration by maximum-likelihood estimation are synergetically
combined and shown to improve the resolution of two-photon excitation microscopy 2–4 

Multichannel regularized iterative restoration of motion compensated image sequences
MG Choi, NP Galatsanos , and Image , 1996 ,
Abstract Restoration of image sequences is an important problem that can be encountered
in many image processing applications, such as, visual communications, robot guidance
and target tracking. The independent restoration of each frame in an image sequence is a 

Blind image restoration based on RBF neural networks
P Guo ,Proceedings of SPIE, 2004 ,
ABSTRACT In this paper, we propose a novel technique for blind image restoration and
resolution enhancement based on radial basis function (RBF) neural network. The RBF
network gives a solution of the regularization problem often seen in function estimation 

Wavelet-constrained image restoration
Image restoration problems can naturally be cast as constrained convex programming
problems in which the constraints arise from a priori information and the observation of
signals physically related to the image to be recovered. In this paper, the focus is placed 

An efficient primal-dual method for l1tv image restoration
Y Dong, M Hintermüller ,SIAM J. Imaging Sci, 2009 ,
Abstract. Image restoration based on an i1-data-fitting term and edge preserving total
variation regularization is considered. The associated non-smooth energy minimization
problem is handled by utilizing Fenchel-duality and dual regularization techniques. The 

Functionals with p (x)-growth in image restoration
Y Chen, S Levine ,SIAM Journal of App. Math, 2006 ,
Abstract. We study a functional of p (x) growth (p (x)= 1) which provides a model for image
denoising, enhancement, and restoration. The diffusion resulting from the proposed model is
a combination of Total Variation based regularization and Gaussian smoothing. The 

Application of image restoration methods for confocal fluorescence microscopy

ABSTRACT The analysis of the three-dimensional structure of tissue, cells and cellular
constituents play a major role in biomedical research. Three-dimensional images, acquired
by confocal fluorescence microscopes play a key role in this analysis. However, the