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Convolutional Neural Networks Deceived by Visual Illusions
[article]
2018
arXiv
pre-print
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Visual illusions teach us that what we see is not always what it is represented in the physical world. Its special nature make them a fascinating tool to test and validate any new vision model proposed. In general, current vision models are based on the concatenation of linear convolutions and non-linear operations. In this paper we get inspiration from the similarity of this structure with the operations present in Convolutional Neural Networks (CNNs). This motivated us to study if CNNs
arXiv:1811.10565v1
fatcat:fcyeob5wjfanpnk23wreqese5a
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... for low-level visual tasks are deceived by visual illusions. In particular, we show that CNNs trained for image denoising, image deblurring, and computational color constancy are able to replicate the human response to visual illusions, and that the extent of this replication varies with respect to variation in architecture and spatial pattern size. We believe that this CNNs behaviour appears as a by-product of the training for the low level vision tasks of denoising, color constancy or deblurring. Our work opens a new bridge between human perception and CNNs: in order to obtain CNNs that better replicate human behaviour, we may need to start aiming for them to better replicate visual illusions.
Perceptual Color Characterization of Cameras
2014
Sensors
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This is why Javier Vazquez-Corral and Marcelo Bertalmío are with the Department of Information and Communications Technologies, Universitat Pompeu Fabra. ...
doi:10.3390/s141223205
pmid:25490586
pmcid:PMC4299059
fatcat:zetxrya66nc2zorl6q2ssamy5i
Synthesizing Visual Illusions Using Generative Adversarial Networks
[article]
2019
arXiv
pre-print
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Visual illusions are a very useful tool for vision scientists, because they allow them to better probe the limits, thresholds and errors of the visual system. In this work we introduce the first ever framework to generate novel visual illusions with an artificial neural network (ANN). It takes the form of a generative adversarial network, with a generator of visual illusion candidates and two discriminator modules, one for the inducer background and another that decides whether or not the
arXiv:1911.09599v1
fatcat:bsxyisecs5fnjlww2zlfe3tuwq
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... ate is indeed an illusion. The generality of the model is exemplified by synthesizing illusions of different types, and validated with psychophysical experiments that corroborate that the outputs of our ANN are indeed visual illusions to human observers. Apart from synthesizing new visual illusions, which may help vision researchers, the proposed model has the potential to open new ways to study the similarities and differences between ANN and human visual perception.
Simultaneous Blind Gamma Estimation
2015
IEEE Signal Processing Letters
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Recently, Vazquez-Corral and Bertalmío [13] proposed a color stabilization method which is based on the imaging formation model presented by Bianco et al. [1] . ...
Following this model, Vazquez-Corral and Bertalmío represent the pixel values as: R G B p1 = A 1 R G B p 1 γ 1 ; R G B p2 = A 2 R G B p 1 γ 2 (2) where A ...
doi:10.1109/lsp.2015.2396299
fatcat:pl3vk2bbvbdy3n4mn54dfean64
Fusion-based Variational Image Dehazing
2016
IEEE Signal Processing Letters
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We propose a novel image dehazing technique based on the minimization of two energy functionals and a fusion scheme to combine the output of both optimizations. The proposed Fusion-based Variational Image Dehazing (FVID) method is a spatially varying image enhancement process that first minimizes a previously proposed variational formulation that maximizes contrast and saturation on the hazy input. The iterates produced by this minimization are kept, and a second energy that shrinks faster
doi:10.1109/lsp.2016.2643168
fatcat:dvbixycvqbhivfbhu54cignccm
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... sity values of well-contrasted regions is minimized, allowing to generate a set of Difference-of-Saturations (DiffSat) maps by observing the shrinking rate. The iterates produced in the first minimization are then fused with these DiffSat maps to produce a haze-free version of the degraded input. The FVID method does not rely on a physical model from which to estimate a depth map, nor it needs a training stage on a database of human-labeled examples. Experimental results on a wide set of hazy images demonstrate that FVID better preserves the image structure on close-by regions that are less affected by fog, and it successfully compares with other current methods in the task of removing haze degradation from far-away regions.
Spectral Sharpening of Color Sensors: Diagonal Color Constancy and Beyond
2014
Sensors
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Vazquez-Corral et al. ...
Building upon Philipona and O'Regan's model, Vazquez-Corral et al. ...
doi:10.3390/s140303965
pmid:24577523
pmcid:PMC4003926
fatcat:zzphrex2zrbaplztv4zzop326m
Enhanced Variational Image Dehazing
2015
SIAM Journal of Imaging Sciences
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Images obtained under adverse weather conditions, such as haze or fog, typically exhibit low contrast and faded colors, which may severely limit the visibility within the scene. Unveiling the image structure under the haze layer and recovering vivid colors out of a single image remains a challenging task, since the degradation is depth-dependent and conventional methods are unable to overcome this problem. In this work, we extend a well-known perception-inspired variational framework for single
doi:10.1137/15m1008889
fatcat:axfgft5xjjhnxid6eohvw4ka64
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... image dehazing. Two main improvements are proposed. First, we replace the value used by the framework for the grey-world hypothesis by an estimation of the mean of the clean image. Second, we add a set of new terms to the energy functional for maximizing the inter-channel contrast. Experimental results show that the proposed Enhanced Variational Image Dehazing (EVID) method outperforms other state-of-the-art methods both qualitatively and quantitatively. In particular, when the illuminant is uneven, our EVID method is the only one that recovers realistic colors, avoiding the appearance of strong chromatic artifacts.
Gamut Mapping through Perceptually-Based Contrast Reduction
[chapter]
2014
Lecture Notes in Computer Science
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In this paper we present a spatial gamut mapping algorithm that relies on a perceptually-based variational framework. Our method adapts a well-known image energy functional whose minimization leads to image enhancement and contrast modification. We show how by varying the importance of the contrast term in the image functional we are able to perform gamut reduction. We propose an iterative scheme that allows our algorithm to successfully map the colors from the gamut of the original image to a
doi:10.1007/978-3-642-53842-1_1
fatcat:5dzyy75cajaxxhwingtwul3bqa
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... iven destination gamut while preserving the colors' perception and texture close to the original image. Both subjective and objective evaluation validate the promising results achieved via our proposed framework.
Physical-based optimization for non-physical image dehazing methods
2020
Optics Express
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Images captured under hazy conditions (e.g. fog, air pollution) usually present faded colors and loss of contrast. To improve their visibility, a process called image dehazing can be applied. Some of the most successful image dehazing algorithms are based on image processing methods but do not follow any physical image formation model, which limits their performance. In this paper, we propose a post-processing technique to alleviate this handicap by enforcing the original method to be
doi:10.1364/oe.383799
pmid:32225542
fatcat:swoayniigvgfzmhlhnvytcli6e
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... with a popular physical model for image formation under haze. Our results improve upon those of the original methods qualitatively and according to several metrics, and they have also been validated via psychophysical experiments. These results are particularly striking in terms of avoiding over-saturation and reducing color artifacts, which are the most common shortcomings faced by image dehazing methods.
A Variational Framework for Single Image Dehazing
[chapter]
2015
Lecture Notes in Computer Science
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Images captured under adverse weather conditions, such as haze or fog, typically exhibit low contrast and faded colors, which may severely limit the visibility within the scene. Unveiling the image structure under the haze layer and recovering vivid colors out of a single image remains a challenging task, since the degradation is depth-dependent and conventional methods are unable to handle this problem. We propose to extend a well-known perception-inspired variational framework [1] for the
doi:10.1007/978-3-319-16199-0_18
fatcat:nzv42pjcwbdjnmz4alv6wjrfl4
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... of single image dehazing. The main modification consists on the replacement of the value used by this framework for the grey-world hypothesis by an estimation of the mean of the clean image. This allows us to devise a variational method that requires no estimate of the depth structure of the scene, performing a spatially-variant contrast enhancement that effectively removes haze from far away regions. Experimental results show that our method competes well with other stateof-the-art methods in typical benchmark images, while outperforming current image dehazing methods in more challenging scenarios.
Dilatación transparietohepática de estenosis biliar benigna: experiencia de 5 años
2010
Cirugia Española
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informa ció n del artí culo Historia del artículo: Recibido el 26 de marzo de 2009 Aceptado el 31 de marzo de 2010 Palabras clave: Estenosis biliar Dilatació n percutá nea transparietohepá tica Dilatació n con baló n Anastomosis bilioenté rica r e s u m e n Objetivo: Valorar los resultados de la dilatació n percutá nea transparietohepá tica de las estenosis biliares benignas durante un período de 5 añ os. Diseñ o: Estudio retrospectivo para evaluar la té cnica, las complicaciones y los
doi:10.1016/j.ciresp.2010.03.044
pmid:20510398
fatcat:uhcasn6kyrfnjepz642kmmpcdq
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... s clínicos, analíticos y radioló gicos. Pacientes: Se recogieron datos de 13 pacientes diagnosticados de estenosis biliar benigna que se trataron mediante dilatació n percutá nea en nuestro centro entre los añ os 2002-2006. Se excluyó a los pacientes diagnosticados de enfermedad maligna y a aquellos pacientes a los que se les colocó una pró tesis. Siete de los pacientes han sido receptores de trasplante hepá tico. Un paciente había recibido dilatació n endoscó pica en 2 ocasiones con persistencia de la estenosis. Resultados: Se comprobó mejoría clínica y radioló gica en el 60% de los casos y analítica en el 69% de los casos (el 61% de normalizació n). El 30% de los casos presentó reestenosis, de los que el 50% fueron subsidiarios de rescate mediante redilatació n. Las complicaciones que se presentaron (30,7%) se resolvieron de forma conservadora. No se observaron diferencias significativas entre el grupo de trasplante y el grupo sin trasplante. Conclusiones: La dilatació n de las estenosis benignas de la vía biliar por vía transparietohepá tica es una té cnica bastante segura, tiene una alta tasa de resolució n a medio plazo y permite evitar la cirugía en má s de un 75% de los pacientes. Los resultados deben confirmarse en muestras mayores. & 2009 AEC. Publicado por Elsevier Españ a, S.L. Todos los derechos reservados. Transparieto-hepatic dilation of benign biliary stenosis: 5 years experience Keywords: Biliary stenosis Transparieto-hepatic percutaneous dilation a b s t r a c t Objective: To assess the results of percutaneous transparieto-hepatic dilation of benign biliary stenosis achieved over a period of 5 years. Design: A retrospective study to assess the technique, complications and the clinical, analytical and radiology results.
Matching visual induction effects on screens of different size
2021
Journal of Vision
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, Mathieu, & Bertalmío
Canham, Vazquez-Corral, Mathieu, & Bertalmío ...
., 2007) and in a color opponent color space like CIELAB (Zamir, Vazquez-Corral & Bertalmío, 2017) , and the results showed that the LHE method has several good properties: (1) It has a very good local ...
doi:10.1167/jov.21.6.10
pmid:34144607
pmcid:PMC8237091
fatcat:27g7jk3wrjervhnf4fqaarzln4
Gamut mapping for visual attention retargeting
2017
Final program and proceedings (Color and Imaging Conference)
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Author Biography Javier Vazquez-Corral received the Ph.D. degree in computer science from the Universitat Autònoma de Barcelona, Bellaterra, Spain, in 2011. ...
doi:10.2352/issn.2169-2629.2017.25.313
fatcat:homrvhdsbze3zmxpf6wqkpv3de
Color matching images with unknown non-linear encodings
2020
IEEE Transactions on Image Processing
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One is the method of Vazquez-Corral and Bertalmío [26] , that relies on finding a sufficiently large number of achromatic matches among source and reference. ...
Vazquez-Corral and Bertalmío [24] proposed a color stabilization algorithm that consists of estimating a power law (γ value) for each of the images, and a single 3 × 3 matrix, to color match the source ...
doi:10.1109/tip.2020.2968766
pmid:32011253
fatcat:ek3poa5jvveuxisykycuwuymiy
Spatial gamut mapping among non-inclusive gamuts
2018
Journal of Visual Communication and Image Representation
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Gamut mapping transforms the color gamut of an image to that of a target device. Two cases are usually considered: gamut reduction (target gamut smaller than source gamut), and gamut extension (target gamut larger than the source gamut). Less attention is devoted to the more general case, when neither gamut is fully included in the other. In this work we unify and expand two recent methods for gamut extension and reduction, so as to simultaneously perform both forms of gamut mapping in
doi:10.1016/j.jvcir.2018.05.012
fatcat:ga7q7et275f57ng43t5beaax7m
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... regions of the same image without introducing color artifacts or halos. We demonstrate the usefulness of this approach for the traditional gamut mapping problem, and also how the proposed method can be used to adapt the color palette of an image so that it is closer to that of a given reference image. Results are compared with the state-of-the-art and validated through user tests and objective metrics.
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