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Joan Verdera

dblp:87/5887 · DBLP profile ↗
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6ranked-venue papers
1as first author
0since 2021 · last 2008
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 4 · 1 first-authorArtificial intelligence and machine learning · 3

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
3 papers
Image and video processing · 100%
Theoretical computer science
1 paper
Mathematical optimization · 100%

Topics — the 6 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Image and video processing
image fusion
0.112006
A Variational Model for P+XS Image Fusion · Int. J. Comput. Vis. 2006
Image and video processing › image restoration
image inpainting
0.122001
Filling-in by joint interpolation of vector fields and gray levels · IEEE Trans. Image Process. 2001
A Variational Model for Filling-In Gray Level and Color Images · ICCV 2001
Image and video processing
image restoration
0.022001
A Variational Model for Filling-In Gray Level and Color Images · ICCV 2001
Filling-in by joint interpolation of vector fields and gray levels · IEEE Trans. Image Process. 2001
Image and video processing › image restoration › image inpainting
variational inpainting
0.012001
Filling-in by joint interpolation of vector fields and gray levels · IEEE Trans. Image Process. 2001
Image and video processing › image fusion › remote sensing image fusion
pansharpening
0.012006
A Variational Model for P+XS Image Fusion · Int. J. Comput. Vis. 2006
Mathematical optimization
variational methods
0.012001
A Variational Model for Filling-In Gray Level and Color Images · ICCV 2001

Methods — techniques the papers use, named apart from their topics

variational model · 0.1variational method · 0.0partial differential equations · 0.0gradient descent · 0.0
YearPublicationVenuePosition
2008 On geometric variational models for inpainting surface holes
Vicent Caselles, Gloria Haro, Guillermo Sapiro, Joan Verdera
Comput. Vis. Image Underst.4
2006 A Variational Model for P+XS Image Fusion
Coloma Ballester, Vicent Caselles, Laura Igual, Joan Verdera, Bernard Rougé
Int. J. Comput. Vis.4
2003 A variational model for disocclusion
abstract
In this paper we study a variational approach for filling-in regions of missing data in 2D and 3D digital images. Applications of this technique include the restoration of old photographs and removal of superimposed text like dates, subtitles, or publicity, or the zooming of images. The approach presented here, initially introduced in [C. Ballester et al., 2001], is based on a joint interpolation of the image gray-levels and gradient/isophotes directions, smoothly extending the isophote lines into the holes of missing data. The process underlying this approach can be considered as an interpretation of the Gestaltist's principle of good continuation. After discussing the model, we present the numerical algorithm used to minimize it and display some numerical experiments.
Coloma Ballester, Vicent Caselles, Joan Verdera
ICIP (3)3
2003 Inpainting surface holes
abstract
An algorithm for filling-in surface holes is introduced in this paper. The basic idea is to represent the surface of interest in implicit form, and fill-in the holes with a system of geometric partial differential equations derived from image inpainting algorithms. The framework and examples with synthetic and real data are presented.
Joan Verdera, Vicent Caselles, Marcelo Bertalmío, Guillermo Sapiro
ICIP (2)1
2001 A Variational Model for Filling-In Gray Level and Color Images
Coloma Ballester, Vicent Caselles, Joan Verdera, Marcelo Bertalmío, Guillermo Sapiro
ICCV3
2001 Filling-in by joint interpolation of vector fields and gray levels
abstract
A variational approach for filling-in regions of missing data in digital images is introduced. The approach is based on joint interpolation of the image gray levels and gradient/isophotes directions, smoothly extending in an automatic fashion the isophote lines into the holes of missing data. This interpolation is computed by solving the variational problem via its gradient descent flow, which leads to a set of coupled second order partial differential equations, one for the gray-levels and one for the gradient orientations. The process underlying this approach can be considered as an interpretation of the Gestaltist's principle of good continuation. No limitations are imposed on the topology of the holes, and all regions of missing data can be simultaneously processed, even if they are surrounded by completely different structures. Applications of this technique include the restoration of old photographs and removal of superimposed text like dates, subtitles, or publicity. Examples of these applications are given. We conclude the paper with a number of theoretical results on the proposed variational approach and its corresponding gradient descent flow.
Coloma Ballester, Marcelo Bertalmío, Vicent Caselles, Guillermo Sapiro, Joan Verdera
IEEE Trans. Image Process.5