A novel algorithm for restoring an optical signal of spatial finite extent, which is subjected to low-pass frequency filtering, is presented. The problem is treated as an algebraic image restoration problem. The algorithm minimizes the L1 norm of the solution vector, subject to the constraints that the solution amplitude values are non-negative and bounded. Physically acceptable solutions of the resulting ill-posed system of equations are obtained by replacing the system by an approximate one of smaller rank. Numerical results show that this algorithm compares favorably with other known methods. Comments and conclusions are given.Peer reviewed: YesNRC publication: Ye
This paper proposes a two-phase fully automatic scheme for restoring images that have been corrupted...
This paper proposes a two-phase fully automatic scheme for restoring images that have been corrupted...
Abstract. Image restoration problems are often solved by finding the minimizer of a suitable objecti...
A method for restoring an optical image which is subjected to low-pass frequency filtering is presen...
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 re-storation of images contaminated by blur an...
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 re-storation of images contaminated by blur an...
We propose an adaptive norm strategy designed for the restora- tion of images contaminated by blur ...
We propose an adaptive norm strategy designed for the restora- tion of images contaminated by blur ...
We propose an adaptive norm strategy designed for the restora- tion of images contaminated by blur ...
We propose an image restoration method. The method generalizes image restoration algorithms that are...
An arithmetic operations (multiplications and divisions) count is presented for three recent algorit...
Image restoration problems are often solved by finding the minimizer of a suitable objective functio...
Methods for the restoration of images corrupted by blur and noise are presented. During transmission...
This paper proposes a two-phase fully automatic scheme for restoring images that have been corrupted...
This paper proposes a two-phase fully automatic scheme for restoring images that have been corrupted...
Abstract. Image restoration problems are often solved by finding the minimizer of a suitable objecti...
A method for restoring an optical image which is subjected to low-pass frequency filtering is presen...
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 re-storation of images contaminated by blur an...
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 re-storation of images contaminated by blur an...
We propose an adaptive norm strategy designed for the restora- tion of images contaminated by blur ...
We propose an adaptive norm strategy designed for the restora- tion of images contaminated by blur ...
We propose an adaptive norm strategy designed for the restora- tion of images contaminated by blur ...
We propose an image restoration method. The method generalizes image restoration algorithms that are...
An arithmetic operations (multiplications and divisions) count is presented for three recent algorit...
Image restoration problems are often solved by finding the minimizer of a suitable objective functio...
Methods for the restoration of images corrupted by blur and noise are presented. During transmission...
This paper proposes a two-phase fully automatic scheme for restoring images that have been corrupted...
This paper proposes a two-phase fully automatic scheme for restoring images that have been corrupted...
Abstract. Image restoration problems are often solved by finding the minimizer of a suitable objecti...