Add to ORKGIn this overview of the recent Curvelet Reconstruction with Sparsity-promoting Inversion (CRSI) method, we present our latest 2-D and 3-D interpolation results on both synthetic and real datasets. We compare these results to interpolated data using other existing methods. Finally, we discuss the challenges related to sparsity-promoting solvers for the large-scale problems the industry faces.Science, Faculty ofEarth and Ocean Sciences, Department ofUnreviewedGraduateFacult
We combine classical concepts from different disciplines — those of α-hull and α-shape from computat...
Purpose: Reconstruction of x-ray computed tomography (CT) data remains a mathematically challenging ...
International audienceIn this paper, we first present a new implementation of the 3-D fast curvelet ...
Incomplete data represents a major challenge for a successful prediction and subsequent removal of m...
Wavefield reconstruction is a crucial step in the seismic processing flow. For instance, unsuccessfu...
A robust data interpolation method using curvelets frames is presented. The advantage of this method...
This article focuses on interpolation subject, in particular, the interpolation of curve bootstrappi...
Interpolation is an ubiquitous technique arising in Mathematics, specially in Numerical Analysis. Th...
Inverse problems are problems where we want to estimate the values of certain parameters of a system...
Abstract. There is a critical need to reconstruct clinically usable images at a low dose. One way of...
This paper describes the application of a first order regularization technique to the problem of rec...
In this dissertation we address the problem of adapting frequency domain tiling using the curvelet t...
Curve reconstruction from noisy point samples is central to surface reconstruction and therefore to ...
The pioneering work on parameter orthogonalization by Cox and Reid (1987) is presented as an inducem...
In this paper we consider the problem of modeling curves in Rn via interpolation without a priori sp...
We combine classical concepts from different disciplines — those of α-hull and α-shape from computat...
Purpose: Reconstruction of x-ray computed tomography (CT) data remains a mathematically challenging ...
International audienceIn this paper, we first present a new implementation of the 3-D fast curvelet ...
Incomplete data represents a major challenge for a successful prediction and subsequent removal of m...
Wavefield reconstruction is a crucial step in the seismic processing flow. For instance, unsuccessfu...
A robust data interpolation method using curvelets frames is presented. The advantage of this method...
This article focuses on interpolation subject, in particular, the interpolation of curve bootstrappi...
Interpolation is an ubiquitous technique arising in Mathematics, specially in Numerical Analysis. Th...
Inverse problems are problems where we want to estimate the values of certain parameters of a system...
Abstract. There is a critical need to reconstruct clinically usable images at a low dose. One way of...
This paper describes the application of a first order regularization technique to the problem of rec...
In this dissertation we address the problem of adapting frequency domain tiling using the curvelet t...
Curve reconstruction from noisy point samples is central to surface reconstruction and therefore to ...
The pioneering work on parameter orthogonalization by Cox and Reid (1987) is presented as an inducem...
In this paper we consider the problem of modeling curves in Rn via interpolation without a priori sp...
We combine classical concepts from different disciplines — those of α-hull and α-shape from computat...
Purpose: Reconstruction of x-ray computed tomography (CT) data remains a mathematically challenging ...
International audienceIn this paper, we first present a new implementation of the 3-D fast curvelet ...