Variational Reconstruction
Variational Reconstruction is a mathematical framework within image reconstruction that formulates the recovery of images from incomplete or noisy data as an optimization problem constrained by a priori regularity conditions, distinguished from other reconstruction methods by its reliance on minimizing an energy functional that balances data fidelity and regularization.
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7.3K
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325
Authors
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Institutions
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2017–2026
40
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A Variational Framework for Retinex
Ron Kimmel, Michael Elad, Doron Shaked et al. · International Journal of Computer Vision · 2003 · 696 citations
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École Polytechnique Fédérale de Lausanne
Lausanne, Switzerland
11 h-index
36 publications
1K citations
University of California, Los Angeles
Los Angeles, United States
5 h-index
13 publications
1.5K citations
Tsinghua University
Beijing, China
4 h-index
8 publications
438 citations
University of Graz
Graz, Austria
4 h-index
7 publications
412 citations
University College London
London, United Kingdom
4 h-index
18 publications
2K citations

Universitat Pompeu Fabra
Barcelona, Spain
4 h-index
7 publications
763 citations
Georgia Institute of Technology
Atlanta, United States
4 h-index
10 publications
209 citations
University of Cambridge
Cambridge, United Kingdom
3 h-index
5 publications
746 citations
1–8 of 161
9 publications · 964 citations
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8 publications · 547 citations
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SIIMS · 7 publications · 260 citations
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6 publications · 271 citations
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4 publications · 142 citations
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