no code implementations • 8 Apr 2024 • Jihanne El Haouari, Jean-Michel Gaucel, Christelle Pittet, Jean-Yves Tourneret, Herwig Wendt
Accurate estimates of Instrument Spectral Response Functions (ISRFs) are crucial in order to have a good characterization of high resolution spectrometers.
no code implementations • 6 Dec 2023 • Clémence Allietta, Jean-Philippe Condomines, Jean-Yves Tourneret, Emmanuel Lochin
Within a Euclidean space, well-known techniques for local outlier detection are based on the Local Outlier Factor (LOF) and its variant, the LoOP (Local Outlier Probability), which incorporates probabilistic concepts to model the outlier level of a data vector.
1 code implementation • 28 Jan 2022 • Florian Mouret, Alexandre Hippert-Ferrer, Frédéric Pascal, Jean-Yves Tourneret
To overcome this issue, a new EM algorithm is investigated for mixtures of elliptical distributions with the property of handling potential missing data.
no code implementations • 22 Oct 2021 • Florian Mouret, Mohanad Albughdadi, Sylvie Duthoit, Denis Kouamé, Guillaume Rieu, Jean-Yves Tourneret
0. 019) is obtained for the imputation of the median Normalized Difference Index (NDVI) of the rapeseed (resp.
no code implementations • 17 Apr 2020 • Florian Mouret, Mohanad Albughdadi, Sylvie Duthoit, Denis Kouamé, Guillaume Rieu, Jean-Yves Tourneret
When using these features with an outlier ratio of 10%, the percentage of detected true positives (i. e., crop anomalies) is equal to 94. 1% for rapeseed parcels and 95. 5% for wheat parcels.
no code implementations • 17 Feb 2020 • Joshua Rapp, Charles Saunders, Julián Tachella, John Murray-Bruce, Yoann Altmann, Jean-Yves Tourneret, Stephen McLaughlin, Robin M. A. Dawson, Franco N. C. Wong, Vivek K Goyal
Non-line-of-sight (NLOS) imaging is a rapidly growing field seeking to form images of objects outside the field of view, with potential applications in search and rescue, reconnaissance, and even medical imaging.
1 code implementation • 21 Jan 2020 • Ricardo Augusto Borsoi, Tales Imbiriba, José Carlos Moreira Bermudez, Cédric Richard, Jocelyn Chanussot, Lucas. Drumetz, Jean-Yves Tourneret, Alina Zare, Christian Jutten
The spectral signatures of the materials contained in hyperspectral images, also called endmembers (EM), can be significantly affected by variations in atmospheric, illumination or environmental conditions typically occurring within an image.
1 code implementation • 26 Jul 2018 • Janka Hatvani, Adrian Basarab, Jean-Yves Tourneret, Miklós Gyöngy, Denis Kouamé
In this article this factorization framework is investigated for single image resolution enhancement with an off-line estimate of the system point spread function.
no code implementations • 18 Sep 2017 • Qi Wei, Emilie Chouzenoux, Jean-Yves Tourneret, Jean-Christophe Pesquet
This paper presents a fast approach for penalized least squares (LS) regression problems using a 2D Gaussian Markov random field (GMRF) prior.
no code implementations • 4 Mar 2017 • Abdelghafour Halimi, Hadj Batatia, Jimmy Le Digabel, Gwendal Josse, Jean-Yves Tourneret
This paper studies a new Bayesian algorithm for the joint reconstruction and classification of reflectance confocal microscopy (RCM) images, with application to the identification of human skin lentigo.
no code implementations • 14 Apr 2016 • Qi Wei, Marcus Chen, Jean-Yves Tourneret, Simon Godsill
In the community of remote sensing, nonlinear mixing models have recently received particular attention in hyperspectral image processing.
no code implementations • 6 Apr 2016 • Qi Wei, Nicolas Dobigeon, Jean-Yves Tourneret, Jose Bioucas-Dias, Simon Godsill
This paper proposes a robust fast multi-band image fusion method to merge a high-spatial low-spectral resolution image and a low-spatial high-spectral resolution image.
no code implementations • 29 Mar 2016 • Qi Wei, Jose Bioucas-Dias, Nicolas Dobigeon, Jean-Yves Tourneret, Marcus Chen, Simon Godsill
The non-negativity and sum-to-one constraints resulting from the intrinsic physical properties of the abundances are introduced as prior information to regularize this ill-posed problem.
no code implementations • 20 Oct 2015 • Pierre-Antoine Thouvenin, Nicolas Dobigeon, Jean-Yves Tourneret
Hyperspectral unmixing is aimed at identifying the reference spectral signatures composing an hyperspectral image and their relative abundance fractions in each pixel.
no code implementations • 1 Oct 2015 • Ningning Zhao, Qi Wei, Adrian Basarab, Nicolas Dobigeon, Denis Kouame, Jean-Yves Tourneret
Specifically, an analytical solution can be obtained and implemented efficiently for the Gaussian prior or any other regularization that can be formulated into an $\ell_2$-regularized quadratic model, i. e., an $\ell_2$-$\ell_2$ optimization problem.
no code implementations • 7 May 2015 • Qi Wei, Jose Bioucas-Dias, Nicolas Dobigeon, Jean-Yves Tourneret
This paper presents a fast spectral unmixing algorithm based on Dykstra's alternating projection.
no code implementations • 17 Apr 2015 • Laetitia Loncan, Luis B. Almeida, José M. Bioucas-Dias, Xavier Briottet, Jocelyn Chanussot, Nicolas Dobigeon, Sophie Fabre, Wenzhi Liao, Giorgio A. Licciardi, Miguel Simões, Jean-Yves Tourneret, Miguel A. Veganzones, Gemine Vivone, Qi Wei, Naoto Yokoya
In this work, we compare new pansharpening techniques designed for hyperspectral data with some of the state of the art methods for multispectral pansharpening, which have been adapted for hyperspectral data.
no code implementations • 18 Mar 2015 • Tales Imbiriba, José Carlos Moreira Bermudez, Cédric Richard, Jean-Yves Tourneret
The detection approach is based on the comparison of the reconstruction errors using both a Gaussian process regression model and a linear regression model.
no code implementations • 10 Feb 2015 • Qi Wei, Nicolas Dobigeon, Jean-Yves Tourneret
This paper proposes a fast multi-band image fusion algorithm, which combines a high-spatial low-spectral resolution image and a low-spatial high-spectral resolution image.
no code implementations • 8 Dec 2014 • Ningning Zhao, Adrian Basarab, Denis Kouame, Jean-Yves Tourneret
Thus, we propose a GGD-Potts model defined by a label map coupling US image segmentation and deconvolution.
no code implementations • 17 Oct 2014 • Sébastien Combrexelle, Herwig Wendt, Nicolas Dobigeon, Jean-Yves Tourneret, Steve McLaughlin, Patrice Abry
Multifractal analysis is a useful signal and image processing tool, yet, the accurate estimation of multifractal parameters for image texture remains a challenge.
no code implementations • 19 Sep 2014 • Qi Wei, José Bioucas-Dias, Nicolas Dobigeon, Jean-Yves Tourneret
This paper presents a variational based approach to fusing hyperspectral and multispectral images.
no code implementations • 1 Oct 2013 • Olivier Besson, Nicolas Dobigeon, Jean-Yves Tourneret
In this letter, we consider two sets of observations defined as subspace signals embedded in noise and we wish to analyze the distance between these two subspaces.
no code implementations • 23 Jul 2013 • Qi Wei, Nicolas Dobigeon, Jean-Yves Tourneret
In this paper, a Bayesian fusion technique for remotely sensed multi-band images is presented.
no code implementations • 6 Apr 2013 • Nicolas Dobigeon, Jean-Yves Tourneret, Cédric Richard, José C. M. Bermudez, Stephen McLaughlin, Alfred O. Hero
When considering the problem of unmixing hyperspectral images, most of the literature in the geoscience and image processing areas relies on the widely used linear mixing model (LMM).