Contributions à des approches informationnelles en imagerie: Traitements conjoints et Résonance stochastique.

Imaging systems are continuously improving and their uses are spreading more and more widely. Imaging systems are based on various physical principles, with a sophistication which keeps enhancing (magnetic resonance imaging, thermography, multi and hyperspectral imaging). Beyond this heterogeneity of constitution, the resulting images share the property of being a support of information. In this context, we propose a contribution to informational approaches in imaging. This is especially guided by a transposition of Shannon's informational paradigm to imaging along two main directions. We present a joint-processing approach where the informational goal of the acquired images is a prior knowledge which is exploited in order to optimize some tuning configurations of the imaging systems. Different joint-processing problems are examined (joint observation scale - estimation, joint compression - estimation, and joint acquisition - compression). We then extend the field of stochastic resonance studies by exploring some new signal-noise mixtures enabling useful noise effects, in coherent imaging and in magnetic resonance imaging. Stochastic resonance is also considered for its specific informational significance (the noise useful to information), as a phenomenon allowing to test and further assess the properties and potentialities of entropic or informational measures applied to imaging. Stochastic resonance is especially used as a benchmark to confront such informational measures to psychovisual measures on images.Les systèmes d'imagerie connaissent un développement soutenu et deviennent de plus en plus largement répandus. Les systèmes d'imagerie mettent en oeuvre des principes physiques variés dont l'élaboration continue de progresser (imagerie par résonance magnétique, thermographie, imagerie multi et hyperspectrale, etc). Au delà de leur constitution physique variée, les images produites ont en commun de constituer un support d'information. Dans ce contexte, nous proposons une contribution à des approches informationnelles en imagerie. Celle-ci est guidée par une transposition du paradigme informationnel de Shannon en imagerie développée selon deux axes. Nous présentons une approche de traitements conjoints où la finalité informationnelle de l'acquisition des images est une donnée connue a priori et utilisée pour optimiser certains réglages de la chaîne d'imagerie. Différentes problématiques de traitements conjoints de l'information sont présentées (échelle d'observation - estimation conjointe, compression - estimation conjointe, et acquisition - compression conjointe). Nous étendons ensuite le champ des études en résonance stochastique en explorant de nouveaux couplages signal-bruit se prêtant à des effets de bruit utile, en imagerie cohérente et en imagerie par résonance magnétique. La résonance stochastique est également considérée, de par sa signification informationnelle spécifique (le bruit utile à l'information), comme un phénomène permettant de tester et d'approfondir l'appréciation des propriétés et potentialités de mesures entropiques ou informationnelles appliquées en imagerie. Elle est en particulier utilisée comme un banc de test pour confronter ces mesures informationnelles à des mesures psychovisuelles sur des images

D.; Tsallis entropy measure of noise-aided information transmission in a binary channel

Noise-aided information transmission via stochastic resonance is shown and analyzed in a binary channel by means of information measures based on the Tsallis entropy. The analysis extends the classic reference of binary information transmission based on the Shannon entropy, and also parallels a recent study based on the Rényi entropy. The conditions for a maximally pronounced stochastic resonance identify optimal Tsallis measures. The study involves a correspondence between Tsallis and Rényi information measures, specially relevant to the characterization of stochastic resonance, and establishing that for such effects identical properties are shared in common by both Tsallis and Rényi measures

Tuning the noise in magnetic resonance imaging to maximize nonlinear information transmission

International audienc

An Image Forgery Detection Solution based on DCT Coefficient Analysis

International audienc

Influence de la structure spatiale des images lors de la quantification de la résonance stochastique dans la perception visuelle

National audienc

Local-feature-based similarity measure for stochastic resonance in visual perception of spatially structured images

International audienceFor images, stochastic resonance or useful-noise effects have previously been assessed with low-level pixel-based information measures. Such measures are not sensitive to coherent spatial structures usually existing in images. As a result, we show that such measures are not sufficient to properly account for stochastic resonance occurring in visual perception. We introduce higher-level similarity measures, inspired from visual perception, and based on local feature descriptors of scale invariant feature transform (SIFT) type. We demonstrate that such SIFT-based measures allow for an assessment of stochastic resonance that matches the visual perception of images with spatial structures. Constructive action of noise is registered in this way with both additive noise and multiplicative speckle noise. Speckle noise, with its grainy appearance, is particularly prone to introducing spurious spatial structures in images, and the stochastic resonance visually perceived and quantitatively assessed with SIFT-based measures is specially examined in this context

Face spoofing attack detection based on the behavior of noises

International audienceThis paper aims to study the problem of spoofing attack detection for facial recognition systems. Real faces and falsified faces present in front of a security system (phone's camera in our case) have differences of micro-textures on their surface, which are exploited to discriminate face spoofing images. Our method exploits the statistic behavior of the distribution of noise's local variances, which performs differently between images of real faces and the fake ones. We test our method on two databases constructed in our laboratory. We used SVM for classification method. Experimental results show that the proposed method has an encouraging performance

A watermarking technique to secure printed QR codes using a statistical test

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Face Spoofing Detection for Smartphones using a 3D Reconstruction and the Motion Sensors

International audienc

Face Spoofing Detection for Smartphones using a 3D Reconstruction and the Motion Sensors

International audienc