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05/19/2023
What You Hear Is What You See: Audio Quality Metrics From Image Quality Metrics
In this study, we investigate the feasibility of utilizing state-of-the-...
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03/17/2023
Disentangling the Link Between Image Statistics and Human Perception
In the 1950s Horace Barlow and Fred Attneave suggested a connection betw...
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02/26/2023
Analysis of Deep Image Quality Models
Subjective image quality measures based on deep neural networks are very...
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06/08/2022
Orthonormal Convolutions for the Rotation Based Iterative Gaussianization
In this paper we elaborate an extension of rotation-based iterative Gaus...
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04/12/2022
Unsupervised Anomaly and Change Detection with Multivariate Gaussianization
Anomaly detection is a field of intense research. Identifying low probab...
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04/07/2022
Inference over radiative transfer models using variational and expectation maximization methods
Earth observation from satellites offers the possibility to monitor our ...
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03/25/2022
Neural Networks with Divisive normalization for image segmentation with application in cityscapes dataset
One of the key problems in computer vision is adaptation: models are too...
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06/08/2021
On the relation between statistical learning and perceptual distances
It has been demonstrated many times that the behavior of the human visua...
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12/22/2020
Learning Structures in Earth Observation Data with Gaussian Processes
Gaussian Processes (GPs) has experienced tremendous success in geoscienc...
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12/09/2020
Disentangling Derivatives, Uncertainty and Error in Gaussian Process Models
Gaussian Processes (GPs) are a class of kernel methods that have shown t...
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12/09/2020
Consistent regression of biophysical parameters with kernel methods
This paper introduces a novel statistical regression framework that allo...
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12/09/2020
Kernel Anomalous Change Detection for Remote Sensing Imagery
Anomalous change detection (ACD) is an important problem in remote sensi...
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12/09/2020
Spatial noise-aware temperature retrieval from infrared sounder data
In this paper we present a combined strategy for the retrieval of atmosp...
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12/07/2020
Randomized kernels for large scale Earth observation applications
Dealing with land cover classification of the new image sources has also...
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12/07/2020
Physics-Aware Gaussian Processes in Remote Sensing
Earth observation from satellite sensory data poses challenging problems...
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12/02/2020
Information Theory in Density Destructors
Density destructors are differentiable and invertible transforms that ma...
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10/13/2020
Gaussianizing the Earth: Multidimensional Information Measures for Earth Data Analysis
Information theory is an excellent framework for analyzing Earth system ...
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10/08/2020
Information Theory Measures via Multidimensional Gaussianization
Information theory is an outstanding framework to measure uncertainty, d...
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07/29/2020
Kernel Methods and their derivatives: Concept and perspectives for the Earth system sciences
Kernel methods are powerful machine learning techniques which implement ...
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06/10/2020
Cross-Sensor Adversarial Domain Adaptation of Landsat-8 and Proba-V images for Cloud Detection
The number of Earth observation satellites carrying optical sensors with...
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05/20/2020
Accounting for Input Noise in Gaussian Process Parameter Retrieval
Gaussian processes (GPs) are a class of Kernel methods that have shown t...
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10/28/2019
PerceptNet: A Human Visual System Inspired Neural Network for Estimating Perceptual Distance
Traditionally, the vision community has devised algorithms to estimate t...
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08/09/2019
Enforcing Perceptual Consistency on Generative Adversarial Networks by Using the Normalised Laplacian Pyramid Distance
In recent years there has been a growing interest in image generation th...
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10/16/2017
Fair Kernel Learning
New social and economic activities massively exploit big data and machin...
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10/06/2017
Eigen-Distortions of Hierarchical Representations
We develop a method for comparing hierarchical image representations in ...
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01/23/2017
Perceptually Optimized Image Rendering
We develop a framework for rendering photographic images, taking into ac...
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11/05/2016
End-to-end Optimized Image Compression
We describe an image compression method, consisting of a nonlinear analy...
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06/02/2016
Sequential Principal Curves Analysis
This work includes all the technical details of the Sequential Principal...
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03/09/2016
Optimized Kernel Entropy Components
This work addresses two main issues of the standard Kernel Entropy Compo...
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01/31/2016
Nonlinearities and Adaptation of Color Vision from Sequential Principal Curves Analysis
Mechanisms of human color vision are characterized by two phenomenologic...
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01/31/2016
Iterative Gaussianization: from ICA to Random Rotations
Most signal processing problems involve the challenging task of multidim...
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01/31/2016
Principal Polynomial Analysis
This paper presents a new framework for manifold learning based on a seq...
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01/31/2016
Image Denoising with Kernels based on Natural Image Relations
A successful class of image denoising methods is based on Bayesian appro...
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01/31/2016