Co-clustering for hyperspectral images.

International audienceClustering is often used for hyperspectral images in order to assign sets of pixels into a number of different homogeneous groups called clusters. As a result, pixels in the same cluster have similar spectra, i.e. are close to each other in a certain sense. Clustering is a core technique of the chemometrics toolbox but some limitations can be pointed for hyperspectral imaging. A first limitation of clustering is that it only considers information in the spectral dimension. Another is that it groups whole vectors. This means that if one or a few elements of the vectors differ significantly, the vectors cannot be clustered together. These limitations may result in suboptimal grouping

Hyperspectral Video Analysis by Motion and Intensity Preprocessing and Subspace Autoencoding

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Study of light-induced formation of photodimers in the i-motif nucleic acid structure by rapid-scan FTIR difference spectroscopy and hybrid hard- and soft-modelling

The i-motif is a DNA structure formed by cytosine-rich sequences, very relevant from a biochemical point of view and potentially useful in Nanotechnology as pH-sensitive nanodevices or nanomotors. To provide a different view on the structural changes and dynamics of direct excitation processes involving i-motif structures, the use of rapid scan FTIR spectroscopy is proposed. Hybrid hard- and soft-modelling based on the Multivariate Curve Resolution by Alternating least squares (MCR-ALS) algorithm has been used for the resolution of rapid-scan FTIR spectra and the interpretation of the photochemically induced time-dependent conformational changes of i-motif structures. The hybrid hard- and soft-modelling version of MCR-ALS (HS-MCR), which allows the introduction of kinetic models to describe the process behavior, provides also rate constants associated with the transitions modeled. The results show that i-motif structures formed by short DNA sequences present higher structural changes upon UV irradiation than those formed by long sequences with additional structural stabilizing elements, such as hairpins

Exploring local spatial features in hyperspectral image

We propose a methodological framework to extract spatial features in hyperspectral imaging data and establish a link between these features and the spectral regions, capturing the observed structural patterns. The proposed approach consists of five main steps: i) two dimensional Stationary Wavelet Transform (2D-SWT) is applied to a hyperspectral data cube, decomposing each single-channel image with a selected wavelet filter up to the maximum decomposition level; ii) a grey-level co-occurrence matrix is calculated for every 2D-SWT image resulting from stage i); iii) distinctive spatial features are determined by computing morphological descriptors from each grey-level co-occurrence matrix; iv) the morphological descriptors are rearranged in a two dimensional data array; v) this data matrix is subjected to Principal Component Analysis (PCA) for exploring the variability of the aforementioned descriptors across spectral channels. As a result, groups of spectral wavelengths associated to specific spatial features can be pointed out yielding a better understanding and interpretation of the data. In principle, this information can also be further exploited, e.g. to improve the separation of pure spectral profiles in a multivariate curve resolution context

Study of conformational transitions of i-motif DNA using time-resolved fluorescence and multivariate analysis methods

Recently, the presence of i-motif structures at C-rich sequences in human cells and their regulatory functions have been demonstrated. Despite numerous steady-state studies on i-motif at neutral and slightly acidic pH, the number and nature of conformation of this biological structure are still controversial. In this work, the fluorescence lifetime of labelled molecular beacon i-motif-forming DNA sequences at different pH values is studied. The influence of the nature of bases at the lateral loops and the presence of a Watson-Crick-stabilized hairpin are studied by means of time-correlated single-photon counting technique. This allows characterizing the existence of several conformers for which the fluorophore has lifetimes ranging from picosecond to nanosecond. The information on the existence of different i-motif structures at different pH values has been obtained by the combination of classical global decay fitting of fluorescence traces, which provides lifetimes associated with the events defined by the decay of each sequence and multivariate analysis, such as principal component analysis or multivariate curve resolution based on alternating least squares. Multivariate analysis, which is seldom used for this kind of data, was crucial to explore similarities and differences of behaviour amongst the different DNA sequences and to model the presence and identity of the conformations involved in the pH range of interest. The results point that, for i-motif, the intrachain contact formation and its dissociation show lifetimes ten times faster than for the open form of DNA sequences. They also highlight that the presence of more than one i-motif species for certain DNA sequences according to the length of the sequence and the composition of the bases in the lateral loop

Résolution et modélisation chimiométrique en spectroscopie moléculaire

Cette Habilitation à Diriger des Recherches présente les concepts et développements en chimiométrie pour la description, la résolution ou la modélisation des données des systèmes physico-chimiques étudiés par spectroscopie moléculaire. Les algorithmes de chimiométrie seront d'abord redéfinis dans un contexte mathématique etstatistique pour justifier l'utilisation qui en est faite en spectroscopie. L'accent sera mis ensuite sur les travaux de recherche et les activités de valorisation autour des deux axes suivants :- l'analyse des systèmes chimiques et physico-chimiques évolutifs, tels que les processus réactionnels photoinduits. L'idée est la description des données spectro-cinétiques par un modèle de structure algébrique bilinéaire, le problème consistant à estimer les contributions cinétiques et spectrales des constituants purs du système chimique. Nous montrons l'intérêt des méthodes multivariées de résolution de courbes pour l'analyse globale des données des systèmes multi-expériences et pour l'intégration d'informations physico-chimiques lors de la résolution. Le résultatest une description adaptée et robuste des données permettant la caractérisation moléculaire des espèces transitoires inconnues. Nous envisageons également les développements vers les méthodes hybrides ou semiparamétriques, en lien avec les approches statistiques développées en traitement du signal.- l'analyse qualitative ou quantitative d'échantillons complexes, multi-composants et soumis à de nombreux facteurs d'influence, tels que les échantillons naturels ou manufacturés. L'idée est la modélisation d'une grandeur obtenue par une méthode de référence à partir d‘observations spectroscopiques des échantillons. L'objectif du modèle construit est la prédiction de cette grandeur lors d'observations ultérieures, pour bénéficier des caractéristiques métrologiques des techniques de spectroscopie. Nous montrons le potentiel des méthodes issues de l'apprentissage statistique. Les développements sont liés à l'écriture de termes de pénalisation de l'erreur empirique, notamment pour le contrôle de la complexité des modèles. Nous insistons sur les méthodes non-paramétriques telles que les machines à vecteurs de support à fonctions noyaux, pour nos applications en spectroscopie, lorsque la dimension des données est problématique

Introducing special issue on chemical image analysis

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