Publications

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G
Gomez-Villa A, Bertalmío M, Malo J.  2020.  Visual information flow in Wilson-Cowan networks. Journal of Neurophysiology. VisualInformation.pdf (3.12 MB)
Gomez-Villa A, Martín A, Vazquez-Corral J, Bertalmío M.  2019.  Convolutional Neural Networks Deceived by Visual Illusions. *Accepted* in Computer Vision and Pattern Recognition (CVPR). CNNillusions.pdf (4.05 MB)
Gomez-Villa A, Martín A, Vazquez-Corral J, Bertalmío M, Malo J.  2020.  Visual Illusions Also Deceive Convolutional Neural Networks: Analysis and Implications. Vision Research. visualIllusions.pdf (3.73 MB)
Ghimpeteanu G, Kane D, Batard T, Levine S, Bertalmío M.  2016.  Local Denoising Based on Curvature Smoothing can Visually Outperform Non-local Methods on Photographs with Actual Noise. IEEE International Conference on Image Processing. DenoisingICIP2016.pdf (1.9 MB)
Ghimpeteanu G, Batard T, Bertalmío M, Levine S.  2014.  Denoising an Image by Denoising its Components in a Moving Frame. International Conference on Image and Signal Processing (ICISP). *Best Paper Award*. icisp00.pdf (6.88 MB)
Ghimpeteanu G, Batard T, Bertalmío M, Levine S.  2015.  A Decomposition Framework for Image Denoising Algorithms. IEEE Transactions on Image Processing. DenoisingTIP.pdf (10.26 MB)
Ghimpeteanu G, Batard T, Seybold T, Bertalmío M.  2016.  Local denoising applied to RAW images may outperform non-local patch-based methods applied to the camera output. IS&T Electronic Imaging Conference. DenoisingEI2016.pdf (2.09 MB)
Galdran A, Vazquez-Corral J, Pardo D, Bertalmío M.  2015.  Enhanced Variational Image Dehazing. SIAM Journal on Imaging Sciences (SIIMS). VariationalDehazing_EVID_final_LR.pdf (15.17 MB)
Galdran A, Vazquez-Corral J, Pardo D, Bertalmío M.  2014.  A variational Framework for Single Image Dehazing. European Conference on Computer Vision Workshops . Galdranetaleccvw.pdf (9.65 MB)
Galdran A, Alvarez-Gila A, Bria A, Vazquez-Corral J, Bertalmío M.  2018.  On the Duality Between Retinex and Image Dehazing. *Accepted* in Computer Vision and Pattern Recognition (CVPR). ImageDehazing.pdf (4.3 MB)
C
Cyriac P, Kane D, Bertalmío M.  2016.  Automatic, Viewing-condition Dependent Contrast Grading Based on Perceptual Models. Society of Motion Picture & Television Engineers Annual Technical Conference & Exhibition. ToneMapping_smpte16.pdf (739.66 KB)
Cyriac P, Batard T, Bertalmío M.  2014.  A Non Local Variational Formulation for the Improvement of Tone Mapped Images. SIAM Journal on Imaging Sciences (SIIMS). ToneMapping.pdf (4.68 MB)
Cyriac P, Kane D, Bertalmío M.  2016.  Optimized Tone Curve for In-Camera Image Processing. IS&T Electronic Imaging Conference. EI16_tmo.pdf (9.55 MB)
Cyriac P, Canham T, Kane D, Bertalmío M.  2020.  Vision models fine-tuned by cinema professionals for High Dynamic Range imaging in movies. Multimedia Tools and Applications. VisionModelsHDR.pdf (2.64 MB)
Cyriac P, Bertalmío M, Kane D, Vazquez-Corral J.  2015.  A Tone Mapping Operator Based on Neural and Psychophysical Models of Visual Perception. Proc. SPIE Human Vision and Electronic Imaging XX. ToneMappingSPIE.pdf (3.59 MB)
Cyriac P, Kane D, Bertalmío M.  2015.  Perceptual Dynamic Range for In-Camera Image Processing. British Machine Vision Conference (BMVC). tonemapping_bmvc.pdf (4.59 MB)
Cyriac P, Batard T, Bertalmío M.  2013.  A Variational Method for the Optimization of Tone Mapping Operators. 6th Pacific-Rim Symposium on Image and Video Technology, Guanajuato, Mexico. TM_PSIVT2013.pdf (5.87 MB)
Cardelino J, Caselles V, Bertalmío M, Randall G.  2013.  A Contrario Selection of Optimal Partitions for Image Segmentation. SIAM Journal on Imaging Sciences (SIIMS). SIIMS_final.pdf (2.56 MB)
Canham T, Vazquez-Corral J, Mathieu E, Bertalmío M.  2020.  Matching visual induction effects on screens of different size by regularizing a neural field model of color appearance. Submitted. visualInductionEffects.pdf (2.63 MB)

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