International audienceThe standard approach to image reconstruction, which consists in minimizing a cost function combining data- fidelity with edge-preserving regularization, tends to pro- duce noisy object boundaries and to create a staircase ef- fect. We propose to incorporate the smoothness of the edge field via an additional penalty term defined in a mul- tiresolution domain. We provide an efficient half-quadratic algorithm to solve the resulting optimization problem, in- cluding the case when the data-fidelity is non-quadratic and the cost function non-convex
Image restoration is often solved by minimizing an energy function consisting of a data-fidelity ter...
Tomographic image reconstruction using statistical methods can provide more accurate system modeling...
We propose a new objective function for the image reconstruction problem, where the image is compris...
International audienceThe standard approach to image reconstruction, which consists in minimizing a ...
International audienceThe standard approach to image reconstruction, which consists in minimizing a ...
The standard approach to image reconstruction is to stabilize the problem by including an edge-prese...
Abstract—A popular way to restore images comprising edges is to minimize a cost function combining a...
We consider the restoration of discrete signals and images using least-squares with nonconvex regula...
Abstract—Many image processing problems are ill posed and must be regularized. Usually, a roughness ...
Abstract. We address the minimization of regularized convex cost functions which are cus-tomarily us...
The article addresses a wide class of image deconvolution or reconstruction situations where a sough...
This paper discusses the problem of superresolution reconstruction. To preserve edges accurately and...
AbstractIn image restoration, the so-called edge-preserving regularization method is used to solve a...
This thesis deals with regularized image reconstruction. We seek images consisting of smoothregions ...
In image restoration, the so-called edge-preserving regularization method is used to solve an optimi...
Image restoration is often solved by minimizing an energy function consisting of a data-fidelity ter...
Tomographic image reconstruction using statistical methods can provide more accurate system modeling...
We propose a new objective function for the image reconstruction problem, where the image is compris...
International audienceThe standard approach to image reconstruction, which consists in minimizing a ...
International audienceThe standard approach to image reconstruction, which consists in minimizing a ...
The standard approach to image reconstruction is to stabilize the problem by including an edge-prese...
Abstract—A popular way to restore images comprising edges is to minimize a cost function combining a...
We consider the restoration of discrete signals and images using least-squares with nonconvex regula...
Abstract—Many image processing problems are ill posed and must be regularized. Usually, a roughness ...
Abstract. We address the minimization of regularized convex cost functions which are cus-tomarily us...
The article addresses a wide class of image deconvolution or reconstruction situations where a sough...
This paper discusses the problem of superresolution reconstruction. To preserve edges accurately and...
AbstractIn image restoration, the so-called edge-preserving regularization method is used to solve a...
This thesis deals with regularized image reconstruction. We seek images consisting of smoothregions ...
In image restoration, the so-called edge-preserving regularization method is used to solve an optimi...
Image restoration is often solved by minimizing an energy function consisting of a data-fidelity ter...
Tomographic image reconstruction using statistical methods can provide more accurate system modeling...
We propose a new objective function for the image reconstruction problem, where the image is compris...