It has been shown in literature that adaptive regu-larized image restoration is superior to non-adaptive one. However, the adaptivity introduced in most pro-posed iterative algorithms is based only on the appli-cation of space-variant smoothing operator. It is found that these adaptive algorithms suffer from insufficient smoothing of the flat image regions. In this paper, an adaptive iterative image restoration algorithm, which applies both techniques of space-variant smoothing and space-variant restoration, is proposed to overcome the stated problem, It is shown by experiments that the re-stored images obtained by the proposed algorithm are better in terms of both numerical measurement and visual quality. 1
Recent work has shown that space-variant regularization in image restoration provides better results...
The image data from imaging system are always degraded by the environment and the imaging sensors. T...
Regularization methods for the solution of ill-posed inverse problems can be successfully applied if...
In this paper the iterative methods of image restoration are considered. These methods are based on ...
In this paper image restoration applications where multiple distorted versions of the same original ...
this paper. Others may involve nonlinear blurring operators, multiplicative noise, noise with more c...
For overcoming the disadvantage of total variation for regularization, which easily produces stair e...
A new version of an iterative scheme of deconvolution originally introduced by Richardson (1972) and...
We propose an adaptive norm strategy designed for the re-storation of images contaminated by blur an...
We propose an adaptive norm strategy designed for the restora- tion of images contaminated by blur ...
In this chapter two new approaches are proposed that address two problems that are commonly encounte...
Abstract We present a new image restoration method by combining iterative VanCittert algorithm with ...
In this paper, we present an adaptive gradient based method to restore images degraded by the effect...
Abstract: Image restoration is an ill-posed inverse problem, which has been introduced the regulariz...
Abstract:- The main idea of image restoration in the blur space is first to obtain a sequence of blu...
Recent work has shown that space-variant regularization in image restoration provides better results...
The image data from imaging system are always degraded by the environment and the imaging sensors. T...
Regularization methods for the solution of ill-posed inverse problems can be successfully applied if...
In this paper the iterative methods of image restoration are considered. These methods are based on ...
In this paper image restoration applications where multiple distorted versions of the same original ...
this paper. Others may involve nonlinear blurring operators, multiplicative noise, noise with more c...
For overcoming the disadvantage of total variation for regularization, which easily produces stair e...
A new version of an iterative scheme of deconvolution originally introduced by Richardson (1972) and...
We propose an adaptive norm strategy designed for the re-storation of images contaminated by blur an...
We propose an adaptive norm strategy designed for the restora- tion of images contaminated by blur ...
In this chapter two new approaches are proposed that address two problems that are commonly encounte...
Abstract We present a new image restoration method by combining iterative VanCittert algorithm with ...
In this paper, we present an adaptive gradient based method to restore images degraded by the effect...
Abstract: Image restoration is an ill-posed inverse problem, which has been introduced the regulariz...
Abstract:- The main idea of image restoration in the blur space is first to obtain a sequence of blu...
Recent work has shown that space-variant regularization in image restoration provides better results...
The image data from imaging system are always degraded by the environment and the imaging sensors. T...
Regularization methods for the solution of ill-posed inverse problems can be successfully applied if...