A second order partial differential operator is applied to an image function. By using a multigrid operator known from the so-called approximation property, we derive a new type of multiresolution decomposition of the image. As an example, the Poisson case is treated in-depth. Using the new transform we devise an algorithm for image fusion. The actual recombination is performed on the image functions on which the partial differential operator has been applied first. A fusion example is elaborated upon. Other applications can be envisaged as well
A variety of new imaging modalities, such as optical diffusion tomography, require the inversion of ...
We propose a novel multiresolution-multigrid based signal reconstruction method from arbitrarily spa...
Abstract. Algebraic Multigrid (AMG) methods were developed originally for nu-merically solving Parti...
A second order partial differential operator is applied to an image function. By using a multigrid o...
A second order partial differential operator is applied to an image function. By using a multigrid o...
A second order partial differential operator is applied to an image function. To this end we conside...
A second order partial differential operator is applied to an image function. To this end we consid...
We briefly describe a multigrid strategy for unilevel and two-level linear systems whose coefficient...
Though the pun in the title is intended, it is not quite fair to Piet Wesseling as he is a person w...
Multigrid methods are studied for solving elliptic partial differential equations. Focus is on paral...
Multigrid technique is a mathematical method which when13; implemented for the numerical solution of...
Many tasks in image processing applications, such as reconstruction, deblurring, and registration, d...
In this paper, we propose a general framework for nonlinear multigrid inversion applicable to any in...
In this paper, we propose a general framework for nonlinear multigrid inversion applicable to any in...
We propose a novel multiresolution-multigrid based signal reconstruction method from arbitrarily spa...
A variety of new imaging modalities, such as optical diffusion tomography, require the inversion of ...
We propose a novel multiresolution-multigrid based signal reconstruction method from arbitrarily spa...
Abstract. Algebraic Multigrid (AMG) methods were developed originally for nu-merically solving Parti...
A second order partial differential operator is applied to an image function. By using a multigrid o...
A second order partial differential operator is applied to an image function. By using a multigrid o...
A second order partial differential operator is applied to an image function. To this end we conside...
A second order partial differential operator is applied to an image function. To this end we consid...
We briefly describe a multigrid strategy for unilevel and two-level linear systems whose coefficient...
Though the pun in the title is intended, it is not quite fair to Piet Wesseling as he is a person w...
Multigrid methods are studied for solving elliptic partial differential equations. Focus is on paral...
Multigrid technique is a mathematical method which when13; implemented for the numerical solution of...
Many tasks in image processing applications, such as reconstruction, deblurring, and registration, d...
In this paper, we propose a general framework for nonlinear multigrid inversion applicable to any in...
In this paper, we propose a general framework for nonlinear multigrid inversion applicable to any in...
We propose a novel multiresolution-multigrid based signal reconstruction method from arbitrarily spa...
A variety of new imaging modalities, such as optical diffusion tomography, require the inversion of ...
We propose a novel multiresolution-multigrid based signal reconstruction method from arbitrarily spa...
Abstract. Algebraic Multigrid (AMG) methods were developed originally for nu-merically solving Parti...