Javier Portilla | CSIC (Consejo Superior de Investigaciones Científicas-Spanish National Research Council) (original) (raw)
Uploads
Papers by Javier Portilla
IEEE Trans. on Aerospace …, 1993
Page 1. Title: TEXTURE SYNTHESIS-BY-ANALYSIS BASED ON A MULTISCALE EARLY-VISION MODEL. Authors:... more Page 1. Title: TEXTURE SYNTHESIS-BY-ANALYSIS BASED ON A MULTISCALE EARLY-VISION MODEL. Authors: Javier Portilla, Rafael Navarro, Oscar Nestares and Antonio Tabernero*. Address: Instituto de Optica (CSIC). Serrano 121. 28006 Madrid. Spain. ...
Abstract. A new texture synthesis-by-analysis method, applying a visu-ally based approach that ha... more Abstract. A new texture synthesis-by-analysis method, applying a visu-ally based approach that has some important advantages over more traditional texture modeling and synthesis techniques is introduced. The basis of the method is to encode the textural information by sampling ...
2020 IEEE 22nd International Workshop on Multimedia Signal Processing (MMSP)
2017 IEEE International Conference on Image Processing, China National Convention Center in Beiji... more 2017 IEEE International Conference on Image Processing, China National Convention Center in Beijing, China, 17-20 September 2017. -- http://2017.ieeeicip.org/Peer Reviewe
ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020
Imaging and Applied Optics 2019 (COSI, IS, MATH, pcAOP), 2019
Proceedings Imaging and Applied Optics 2019, Munich, Germany, 24–27 June 201
Computational Optics II, 2018
Journal of Modern Optics, 2020
2017 IEEE International Conference on Image Processing (ICIP), 2017
Optical Design and Fabrication 2017 (Freeform, IODC, OFT), 2017
2006 14th European Signal Processing Conference, 2006
We present a generic Bayesian framework for signal estimation that incorporates into the cost fun... more We present a generic Bayesian framework for signal estimation that incorporates into the cost function a perceptual metric. We apply this framework to image denoising, considering additive noise of known density. Under certain assumptions on the way local differences in visual responses add up into a global perceptual distance, we obtain analytical solutions that exhibit interesting theoretical properties. We demonstrate through simulations, using an infomax nonlinear perceptual mapping of the input and a local Gaussian model, that in the absence of a prior the new solutions provide a significant improvement on the visual quality of the estimation. Furthermore, they also improve in Mean Square Error terms w.r.t. their non-perceptual counterparts.
Journal of the Optical Society of America A, 2017
ACM Transactions on Graphics, 2016
We propose a method to simulate the rich, scale-dependent dynamics of water waves. Our method pre... more We propose a method to simulate the rich, scale-dependent dynamics of water waves. Our method preserves the dispersion properties of real waves, yet it supports interactions with obstacles and is computationally efficient. Fundamentally, it computes wave accelerations by way of applying a dispersion kernel as a spatially variant filter, which we are able to compute efficiently using two core technical contributions. First, we design novel, accurate, and compact pyramid kernels which compensate for low-frequency truncation errors. Second, we design a shadowed convolution operation that efficiently accounts for obstacle interactions by modulating the application of the dispersion kernel. We demonstrate a wide range of behaviors, which include capillary waves, gravity waves, and interactions with static and dynamic obstacles, all from within a single simulation.
Ophthalmic and Physiological Optics, 2016
This paper introduces a new texture synthesis-by-analysis method, applying a visual-based approac... more This paper introduces a new texture synthesis-by-analysis method, applying a visual-based approach which has some important advantages over more traditional texture modeling and synthesis techniques. The basis of the method is to encode the textural information by sampling both the power spectrum and the histogram of homogeneously textured images. The spectrum is sampled in a log-polar grid by using a pyramid Gabor scheme. The input image is split into a set of 16 Gabor channels (using four spatial frequency levels and four orientations), plus a low-pass residual (LPR). The energy and equivalent bandwidths of each channel, as well as the LPR power spectrum and the histogram, are measured and the latter two are compressed. The synthesis process consists of generating 16 Gabor filtered independent noise signals with spectral centers equal to those of the Gabor filters, whose energy and equivalent bandwidths are calculated in order to reproduce the measured values. These band-pass sign...
IEEE International Conference on Image Processing 2005, 2005
IEEE Trans. on Aerospace …, 1993
Page 1. Title: TEXTURE SYNTHESIS-BY-ANALYSIS BASED ON A MULTISCALE EARLY-VISION MODEL. Authors:... more Page 1. Title: TEXTURE SYNTHESIS-BY-ANALYSIS BASED ON A MULTISCALE EARLY-VISION MODEL. Authors: Javier Portilla, Rafael Navarro, Oscar Nestares and Antonio Tabernero*. Address: Instituto de Optica (CSIC). Serrano 121. 28006 Madrid. Spain. ...
Abstract. A new texture synthesis-by-analysis method, applying a visu-ally based approach that ha... more Abstract. A new texture synthesis-by-analysis method, applying a visu-ally based approach that has some important advantages over more traditional texture modeling and synthesis techniques is introduced. The basis of the method is to encode the textural information by sampling ...
2020 IEEE 22nd International Workshop on Multimedia Signal Processing (MMSP)
2017 IEEE International Conference on Image Processing, China National Convention Center in Beiji... more 2017 IEEE International Conference on Image Processing, China National Convention Center in Beijing, China, 17-20 September 2017. -- http://2017.ieeeicip.org/Peer Reviewe
ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020
Imaging and Applied Optics 2019 (COSI, IS, MATH, pcAOP), 2019
Proceedings Imaging and Applied Optics 2019, Munich, Germany, 24–27 June 201
Computational Optics II, 2018
Journal of Modern Optics, 2020
2017 IEEE International Conference on Image Processing (ICIP), 2017
Optical Design and Fabrication 2017 (Freeform, IODC, OFT), 2017
2006 14th European Signal Processing Conference, 2006
We present a generic Bayesian framework for signal estimation that incorporates into the cost fun... more We present a generic Bayesian framework for signal estimation that incorporates into the cost function a perceptual metric. We apply this framework to image denoising, considering additive noise of known density. Under certain assumptions on the way local differences in visual responses add up into a global perceptual distance, we obtain analytical solutions that exhibit interesting theoretical properties. We demonstrate through simulations, using an infomax nonlinear perceptual mapping of the input and a local Gaussian model, that in the absence of a prior the new solutions provide a significant improvement on the visual quality of the estimation. Furthermore, they also improve in Mean Square Error terms w.r.t. their non-perceptual counterparts.
Journal of the Optical Society of America A, 2017
ACM Transactions on Graphics, 2016
We propose a method to simulate the rich, scale-dependent dynamics of water waves. Our method pre... more We propose a method to simulate the rich, scale-dependent dynamics of water waves. Our method preserves the dispersion properties of real waves, yet it supports interactions with obstacles and is computationally efficient. Fundamentally, it computes wave accelerations by way of applying a dispersion kernel as a spatially variant filter, which we are able to compute efficiently using two core technical contributions. First, we design novel, accurate, and compact pyramid kernels which compensate for low-frequency truncation errors. Second, we design a shadowed convolution operation that efficiently accounts for obstacle interactions by modulating the application of the dispersion kernel. We demonstrate a wide range of behaviors, which include capillary waves, gravity waves, and interactions with static and dynamic obstacles, all from within a single simulation.
Ophthalmic and Physiological Optics, 2016
This paper introduces a new texture synthesis-by-analysis method, applying a visual-based approac... more This paper introduces a new texture synthesis-by-analysis method, applying a visual-based approach which has some important advantages over more traditional texture modeling and synthesis techniques. The basis of the method is to encode the textural information by sampling both the power spectrum and the histogram of homogeneously textured images. The spectrum is sampled in a log-polar grid by using a pyramid Gabor scheme. The input image is split into a set of 16 Gabor channels (using four spatial frequency levels and four orientations), plus a low-pass residual (LPR). The energy and equivalent bandwidths of each channel, as well as the LPR power spectrum and the histogram, are measured and the latter two are compressed. The synthesis process consists of generating 16 Gabor filtered independent noise signals with spectral centers equal to those of the Gabor filters, whose energy and equivalent bandwidths are calculated in order to reproduce the measured values. These band-pass sign...
IEEE International Conference on Image Processing 2005, 2005