Jean-François Aujol focuses on Image processing, Image restoration, Mathematical analysis, Algorithm and Mathematical optimization. Image processing is a subfield of Artificial intelligence that he tackles. As a part of the same scientific study, Jean-François Aujol usually deals with the Image restoration, concentrating on Dykstra's projection algorithm and frequently concerns with Topology, Variable and Bounded variation.
His studies examine the connections between Mathematical analysis and genetics, as well as such issues in Image, with regards to Calculus of variations and Uniqueness. His studies in Algorithm integrate themes in fields like Norm and Hilbert space. His Mathematical optimization research incorporates elements of Efficient algorithm and Color normalization.
His primary areas of investigation include Artificial intelligence, Computer vision, Algorithm, Image and Image processing. His work in Artificial intelligence addresses issues such as Pattern recognition, which are connected to fields such as Noise reduction. As a member of one scientific family, Jean-François Aujol mostly works in the field of Computer vision, focusing on Lidar and, on occasion, Point.
The study incorporates disciplines such as Photometric stereo, Boundary, Image restoration and Texture synthesis in addition to Algorithm. Jean-François Aujol has included themes like Simple, Luminance, Mathematical analysis and Topographic map in his Image study. His Image processing study integrates concerns from other disciplines, such as Norm, Feature extraction and Mathematical optimization.
His main research concerns Artificial intelligence, Computer vision, Algorithm, Applied mathematics and Image. His study in the fields of Image colorization and Variety under the domain of Artificial intelligence overlaps with other disciplines such as Prior probability, Relation and Focus. In his study, which falls under the umbrella issue of Computer vision, Point cloud and Point is strongly linked to Lidar.
His Algorithm research is multidisciplinary, incorporating perspectives in Principal component analysis and Fourier transform. Jean-François Aujol combines subjects such as Image resolution, Machine learning, Multispectral image and Pattern recognition with his study of Image. His Segmentation study combines topics from a wide range of disciplines, such as Margin and Image processing.
Jean-François Aujol spends much of his time researching Applied mathematics, Computer vision, Artificial intelligence, Segmentation and Minification. His work on Ode as part of general Applied mathematics study is frequently linked to Convex optimization, Rate of convergence and Flatness, therefore connecting diverse disciplines of science. His Computer vision research incorporates themes from Margin and Lidar.
His research integrates issues of Descent, Heuristics and Greedy algorithm in his study of Minification. His Point cloud research includes themes of Image, Task and Feature extraction. His studies deal with areas such as End-to-end principle, Point and Image segmentation as well as Image processing.
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Structure-Texture Image Decomposition--Modeling, Algorithms, and Parameter Selection
Jean-François Aujol;Guy Gilboa;Tony Chan;Stanley Osher.
International Journal of Computer Vision (2006)
A Variational Approach to Removing Multiplicative Noise
Gilles Aubert;Jean-François Aujol.
Siam Journal on Applied Mathematics (2008)
Dual Norms and Image Decomposition Models
Jean-François Aujol;Antonin Chambolle.
International Journal of Computer Vision (2005)
Image Decomposition into a Bounded Variation Component and an Oscillating Component
Jean-François Aujol;Gilles Aubert;Laure Blanc-Féraud;Antonin Chambolle.
Journal of Mathematical Imaging and Vision (2005)
Some First-Order Algorithms for Total Variation Based Image Restoration
Journal of Mathematical Imaging and Vision (2009)
Regularized Discrete Optimal Transport
Sira Ferradans;Nicolas Papadakis;Gabriel Peyré;Jean-François Aujol.
Siam Journal on Imaging Sciences (2014)
Adaptive regularization of the NL-means: Application to image and video denoising
Camille Sutour;Charles-Alban Deledalle;Jean-François Aujol.
IEEE Transactions on Image Processing (2014)
Modeling very oscillating signals. Application to image processing
Gilles Aubert;Jean-Francois Aujol;Jean-Francois Aujol.
Applied Mathematics and Optimization (2005)
Exemplar-Based Inpainting from a Variational Point of View
Jean-François Aujol;Saïd Ladjal Ladjal;Simon Masnou.
Siam Journal on Mathematical Analysis (2010)
Color image decomposition and restoration
Jean-François Aujol;Sung Ha Kang.
Journal of Visual Communication and Image Representation (2006)
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