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Visual illusions via neural dynamics: Wilson-Cowan-type models and the efficient representation principle. Journal of Neurophysiology.. 2020.
Denoising an Image by Denoising its Curvature Image. SIAM Journal on Imaging Sciences (SIIMS).. 2013.
The Wilson-Cowan Model Describes Contrast Response and Subjective Distortion. Vision Sciences Society Annual Meeting.. 2017.
A model of color constancy and efficient coding can predict lightness induction. Vision Sciences Society Annual Meeting.. 2014.
Correcting for Induction Phenomena on Displays of Differrent Size. Vision Sciences Society Annual Meeting.. 2016.
From Image Processing to Computational Neuroscience: A Neural Model Based on Histogram Equalization. Frontiers in Computational Neuroscience. 8(71). 2014.
A cortical-inspired model for orientation-dependent contrast perception: a link with Wilson-Cowan equations. Scale Space and Variational Methods in Computer Vision (SSVM2019).. 2019.
Color matching for stereoscopic cinema. Proceedings of Mirage 2013, 6th International Conference on Computer Vision / Computer Graphics Collaboration Techniques and Applications. Berlin.. 2013.
Evidence for the intrinsically nonlinear nature of receptive fields in vision. Scientific reports.. 2020.
Image Processing for Cinema. Chapman & Hall/CRC Mathematical and Computational Imaging Sciences Series.. 2014.
A Variational Approach for the Fusion of Exposure Bracketed Pairs. IEEE Transactions on Image Processing.. 2013.
Connections between Retinex, neural models and variational methods. IS&T Electronic Imaging Conference.. 2016.
Cortical-inspired Wilson-Cowan-type equations for orientation-dependent contrast perception modelling. Journal of Mathematical Imaging and Vision.. 2020.
A Geometric Model of Brightness Perception and its Application to Color Images Correction. *Accepted* in Journal of Mathematical Imaging and Vision.. 2018.
Duality Principle for Image Regularization and Perceptual Color Correction Models. Proceedings of International Conference on Scale Space and Variational Methods in Computer Vision (SSVM).. 2015.
A connection between image processing and artificial neural networks layers through a geometric model of visual perception. Scale Space and Variational Methods in Computer Vision (SSVM2019).. 2019.
Harmonic Flow for Histogram Matching. Geometric Computation for Computer Vision GCCV, Guanajuato, Mexico.. 2013.
A Class of Nonlocal Variational Problems on a Vector Bundle for Color Image Local Contrast Reduction/Enhancement. *Accepted* in Geometry, Imaging and Computing.. 2016.
Generalized Gradient on Vector Bundle - Application to Image Denoising. Proceedings of International Conference on Scale Space and Variational Methods in Computer Vision (SSVM-2013), Austria.. 2013.
On Covariant Derivatives and Their Applications to Image Regularization. SIAM Journal on Imaging Sciences (SIIMS).. 2014.