image restoration-21




Three dimensional biological microscopic image restoration with adaptive local regularization parameter based on wavelet domain
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C Hua ,Proc. of SPIE Vol, 2007 ,144.206.159.178
ABSTRACT A method is proposed for adaptively choosing local regularization parameter
based on gray scale difference estimation, and used to three-dimensional (3D) biological
microscopic image restoration MPMAP algorithm. Every optical-sectioning image of 3D 

Image restoration via Wiener filtering with improved noise estimation
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H Furuya, S Eda ,Proceedings of the 8th WSEAS , 2009 ,wseas.us
Abstract: In this paper, first, the performance of the Wiener filter in the frequency domain for
image restoration is compared with that in the time domain for images degraded by white
noise. After finding that the Wiener filter in the frequency domain is better than that in the 

Subspace Information Criterion for Image Restoration-Mean Squared Error Estimator for Linear Filters
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ABSTRACT Most of the image restoration filters proposed so far include parameters that
control the restoration properties. For bringing out the optimal restoration performance, these
parameters should be determined so that a certain error measure such as the mean 

Critical variable exponent functionals in image restoration
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P Harjulehto, P Hästö, V Latvala ,Preprint, 2011 ,helsinki.fi
ABSTRACT. We study a variable exponent model for image restoration in the case that the
exponent attains the critical value one. We prove existence and G-convergence. The results
answer an open question by Li, Li and Pi [Variable exponent functionals in image

Effect of Neighbourhood Size on Negative Weights in Punctual Kriging based Image Restoration
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A Chaudhry ,Proceedings of world academy of science, , 2007 ,waset.ac.nz
Abstract—We present a general comparison of punctual kriging based image restoration for
different neighbourhood sizes. The formulation of the technique under consideration is
based on punctual kriging and fuzzy concepts for image restoration in spatial domain. 

Multicomponent Image Restoration, an Experimental Study
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A Duijster, S De Backer  Image Analysis and Recognition, 2007 ,Springer
In this paper, we study the problem of restoring multicomponent images. In particular, we
investigate the effects of accounting for the correlation between the image components on
the deconvolution and denoising steps. The proposed restoration is a 2-step procedure, 

NOISE ENHANCED ANISOTROPIC DIFFUSION FOR SCALAR IMAGE RESTORATION
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on Physics in Signal and Image , 2007 ,ahistace.chez-alice.fr
ABSTRACT We demonstrate the possibility of improving the standard Perona-Malik’s
anisotropic diffusion process for image restoration thanks to a constructive action of a
purposely injected noise. The effect is shown to be robustly preserved for various types of 

The realtime parallel system based on dual DSPs for remote sensing image restorationusing time-varying wavelet packets
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Z Jian, N Guo-qiang, L Min-qi, C Xiao-di ,Proc. of SPIE , 2005 ,sutlib2.sut.ac.th
ABSTRACT Considering the fact that the remote sensing image is mainly captured by a
linear CCD with the push-broom way which the image varies over time, the time-varying
wavelet packets for image restoration is proposed in the paper. On one hand, the result of 

A Gaussian Mixture Model-based regularization method in adaptive image restoration
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P Liu, Y Zhang ,Journal of Electronics (China), 2007 ,Springer
Abstract A GMM (Gaussian Mixture Model) based adaptive image restoration is proposed in
this paper. The feature vectors of pixels are selected and extracted. Pixels are clustered into
smooth, edge or detail texture region according to variance-sum criteria function of the 

Prefiltering: Reducing the noise sensitivity of non-linear image restoration algorithms
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GMP Van Kempen ,2001 ,qi.tnw.tudelft.nl
Abstract This paper shows how the performance of image processing algorithms can be
improved by reducing the noise influence on the restoration. A procedure, which we call
prefiltering, reduces this noisy sensitivity after the image has been acquired. It uses a local 

An Algebraic Approach to Two-Dimensional Digital Image Restoration
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COST, 1994 ,ldos.fe.uni-lj.si
Abstract Characteristical problem of multidimensional signal analysis and restoration is
processing of extremely big amounts of data as well as handling of data dependancies in
more than one direction. The problem of restoration can often be described as an ill-

Frequency domain adaptive iterative image restoration and evaluation of the regularization parameter
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MG Kang ,Society of Photo-Optical , 1992 ,ivpl.ece.northwestern.edu
ABSTRACT In this paper a nonlinear frequency domain adaptive regularized iterative image
restoration algorithm is proposed, according to which the regularization parameter is
frequency dependent and is updated at each iteration step. The development of the 

A blind image restoration for out-of-focus blurred images using adaptive inverse filters
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T Imai, R Miyakoshi ,Proceedings of the 4th WSEAS , 2005 ,wseas.us
Abstract: This paper presents a new restoration approach to blurred images using inverse
filters optimized by a Genetic Algorithm (GA). The proposed approach consists of two
procedures. The first is to estimate a degradation level of blurred images based on 

The sine transform operator in the Banach space of symmetric matrices and its application inimage restoration
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K Kou, X Jin ,Numer. Math. J. Chinese Univ, 1999 ,fst.umac.mo
Abstract. In this paper, we study an operator s which maps every n-by-n symmetric matrix An
to a matrix s (An) that minimizes Bn- An F over the set of all matrices Bn that can be
diagonalized by the sine transform. The matrix s (An), called the optimal sine transform 

«A Memory Gradient Algorithm for l2-l0 Regularization with Applications to Image Restoration»
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E Chouzenoux, JC Pesquet   Proc. IEEE ICIP ,www-syscom.univ-mlv.fr
ABSTRACT In this paper, we consider a class of differentiable criteria for sparse image
recovery problems. The regularization is applied to a linear transform of the target image. As
special cases, it includes edge preserving measures or frame analysis potentials. As 

A fast GEM algorithm for Bayesian wavelet-based image restoration using a class of heavy-tailed priors
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Energy Minimization Methods in Computer Vision and , 2003 ,Springer
The paper introduces modelling and optimization contributions on a class of Bayesian
wavelet-based image deconvolution problems. Main assumptions of this class are: 1) space-
invariant blur and additive white Gaussian noise; 2) prior given by a linear (finite of infinite) 
.

Explicit nonflat time evolution for PDE-based image restoration
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S Kim ,Computer Vision, Graphics and Image Processing, 2006 ,Springer
This article is concerned with new strategies with which explicit time-stepping procedures of
PDE-based restoration models converge with a similar efficiency to implicit algorithms.
Conventional explicit algorithms often require hundreds of iterations to converge. In order 


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