Bias-Reduction in Variational Regularization

The aim of this paper is to introduce and study a two-step debiasing method for variational regularization. After solving the standard variational problem, the key idea is to add a consecutive debiasing step minimizing the data fidelity on an appropriate set, the so-called model manifold. The latter is defined by Bregman distances or infimal convolutions thereof, using the (uniquely defined) subgradient appearing in the optimality condition of the variational method. For particular settings, such as anisotropic $\ell^1$ and TV-type regularization, previously used debiasing techniques are shown to be special cases. The proposed approach is however easily applicable to a wider range of regularizations. The two-step debiasing is shown to be well-defined and to optimally reduce bias in a certain setting. In addition to visual and PSNR-based evaluations, different notions of bias and variance decompositions are investigated in numerical studies. The improvements offered by the proposed scheme are demonstrated and its performance is shown to be comparable to optimal results obtained with Bregman iterations.Comment: Accepted by JMI

Vision nocturne numérique : restauration automatique et recalage multimodal des images à bas niveau de lumière

Night vision for helicopter pilots is artificially enhanced by a night vision system. It consists in a light intensifier (LI) coupled with a numerical camera, and an infrared camera. The goal of this thesis is to improve this device by analyzing the defaults in order to correct them.The first part consists in reducing the noise level on the LI images. This requires to evaluate the nature of the noise corrupting these images, so an automatic noise estimation method has been developed. The estimation is based on a non parametric detection of homogeneous areas.Then the noise statistics are estimated using these homogeneous regions by performing a robust l`1 estimation of the noise level function.The LI images can then be denoised using the noise estimation. We have developed in the second part a denoising algorithm that combines the non local means with variational methods by applying an adaptive regularization weighted by a non local data fidelity term. Then this algorithm is adapted to video denoising using the redundancy provided by the sequences, hence guaranteeing temporel stability and preservation of the fine structures.Finally, in the third part data from the optical and infrared sensors are registered. We propose an edge based multimodal registration metric. Combined with a gradient ascent resolution and a temporel scheme, the proposed method allows robust registration of the two modalities for later fusion.La vision de nuit des pilotes d’hélicoptère est artificiellement assistée par un dispositif de vision bas niveau de lumière constitué d’un intensificateur de lumière (IL) couplé à une caméra numérique d’une part, et d’une caméra infrarouge (IR) d’autre part. L’objectif de cette thèse est d’améliorer ce dispositif en ciblant les défauts afin de les corriger.Une première partie consiste à réduire le bruit dont souffrent les images IL. Cela nécessite d’évaluer la nature du bruit qui corrompt ces images. Pour cela, une méthode d’estimation automatique du bruit est mise en place. L’estimation repose sur la détection non paramétrique de zones homogènes de l’image. Les statistiques du bruit peuvent être alors être estimées à partir de ces régions homogènes à l’aide d’une méthode d’estimation robuste de la fonction de niveau de bruit par minimisation l1.Grâce à l’estimation du bruit, les images IL peuvent alors débruitées. Nous avons pour cela développé dans la seconde partie un algorithme de débruitage d’images qui associe les moyennes non locales aux méthodes variationnelles en effectuant une régularisation adaptative pondérée parune attache aux données non locale. Une adaptation au débruitage de séquences d’images permet ensuite de tenir compte de la redondance d’information apportée par le flux vidéo, en garantissant stabilité temporelle et préservation des structures fines.Enfin, dans la troisième partie les informations issues des capteurs optique et infrarouge sont recalées dans un même référentiel. Nous proposons pour cela un critère de recalage multimodal basé sur l’alignement des contours des images. Combiné à une résolution par montée de gradient et à un schéma temporel, l’approche proposée permet de recaler de façon robuste les deuxmodalités, en vue d’une ultérieure fusion

Chemical composition of laurencia obtusa extract and isolation of a new C15-acetogenin

A new C15-acetogenin, sagonenyne (20), exhibiting an unusual single tetrahydropyran ring was isolated from an ethyl acetate extract of Laurencia obtusa collected on the Corsican coastline. Its structure was established by detailed NMR spectroscopic analysis, mass spectrometry, and comparison with literature data. Twenty-three known compounds were identified in the same extract by means of column chromatography steps, using a (13)C-NMR computer aided method developed in our laboratory. In addition to sesquiterpenes, which represent the main chemical class of this extract, diterpenes, sterols, and C15-acetogenins were identified. The crude extract was submitted to a cytotoxicity assay and was particularly active against THP-1 cells, a human leukemia monocytic cell line.info:eu-repo/semantics/publishedVersio

Mentha suaveolens Ehrh. (lamiaceae) essential oil and Its main constituent piperitenone oxide: biological activities and chemistry

Since herbal medicines play an important role in the treatment of a wide range of diseases, there is a growing need for their quality control and standardization. Mentha suaveolens Ehrh. (MS) is an aromatic herb with fruit and a spearmint flavor, used in the Mediterranean areas as a traditional medicine. It has an extensive range of biological activities, including cytotoxic, antimicrobial, antioxidant, anti-inflammatory, hypotensive and insecticidal properties, among others. This study aims to review the scientific findings and research reported to date on MS that prove many of the remarkable various biological actions, effects and some uses of this species as a source of bioactive natural compounds. On the other hand, piperitenone oxide (PO), the major chemical constituent of the carvone pathway MS essential oil, has been reported to exhibit numerous bioactivities in cells and animals. Thus, this integrated overview also surveys and interprets the present knowledge of chemistry and analysis of this oxygenated monoterpene, as well as its beneficial bioactivities. Areas for future research are suggested

Mentha suaveolens Ehrh. Chemotypes in Eastern Iberian Peninsula: Essential Oil Variation and Relation with Ecological Factors

[EN] Essential oil (EO) extracts coming from two representative populations of Mentha suaveolens Ehrh. subesp. suaveolens in Eastern Iberian Peninsula were analyzed by gas chromatography coupled with mass spectrometry and flame ion detector. Plant sampling was carried out in the morning and evening in order to study diurnal variation in EO profiles. Likewise, leaves and inflorescences were analyzed separately. Two chemotypes corresponding to each one of the populations were identified, with piperitenone oxide (35.2 - 74.3%) and piperitone oxide (83.9 - 91.3%), respectively, as major compounds. Once different chemotypes were identified, canonical correspondence analysis was employed to evaluate the effect of the bioclimatic and edaphic factors recorded in each location on the observed differences. Statistical analysis suggested that these chemotypes were closely related to specific environmental factors, mainly the bioclimatic ones. Concretely, piperitenone oxide chemotype can be associated to supramediterranean bioclimatic conditions and soils with major salinity and water field capacity. On the other hand, the most volatile fraction (hydrocarbon monoterpenes) reached its higher level in the morning; specifically, a noticeable amount of limonene was found in morning samples of flowers (4.8 - 10.6%). This fact can be related to ecological role of volatile compounds in order to attract pollinator insects.Llorens Molina, JA.; Rivera Seclén, CF.; Vacas González, S.; Boira Tortajada, H. (2017). Mentha suaveolens Ehrh. Chemotypes in Eastern Iberian Peninsula: Essential Oil Variation and Relation with Ecological Factors. Chemistry & Biodiversity. 14(12):1-9. doi:10.1002/cbdv.201700320S19141

Plants of genus Mentha: From farm to food factory

Genus Mentha, a member of Lamiaceae family, encompasses a series of species used on an industrial scale and with a well-described and developed culture process. Extracts of this genus are traditionally used as foods and are highly valued due to the presence of significant amounts of antioxidant phenolic compounds. Many essential oil chemotypes show distinct aromatic flavor conferred by different terpene proportions. Mint extracts and their derived essential oils exert notable effects against a broad spectrum of bacteria, fungi or yeasts, tested both in vitro or in various food matrices. Their chemical compositions are well-known, which suggest and even prompt their safe use. In this review, genus Mentha plant cultivation, phytochemical analysis and even antimicrobial activity are carefully described. Also, in consideration of its natural origin, antioxidant and antimicrobial properties, a special emphasis was given to mint-derived products as an interesting alternative to artificial preservatives towards establishing a wide range of applications for shelf-life extension of food ingredients and even foodstuffs. Mentha cultivation techniques markedly influence its phytochemical composition. Both extracts and essential oils display a broad spectrum of activity, closely related to its phytochemical composition. Therefore, industrial implementation of genus Mentha depends on its efficacy, safety and neutral taste.This work was supported by the Vice-chancellor for Research Affairs of Shahid Beheshti University of Medical Sciences, Tehran, Iran and Vicerrectoría de Investigación y Desarrollo from University of Concepción, Chile (216.073.031-1.0IN and 217.073.033-1.0). A. Sureda was supported by the Programme of Promotion of Biomedical Research and Health Sciences (CIBEROBN CB12/03/30038). Acknowledgments: N.M. thank to Portuguese Foundation for Science and Technology (FCT–Portugal) for the Strategic project ref. UID/BIM/04293/2013 and “NORTE2020-Programa Operacional Regional do Norte” (NORTE-01-0145-FEDER-000012)

Numerical night vision system : Automatic restoration and multimodal registration of low light level images

La vision de nuit des pilotes d’hélicoptère est artificiellement assistée par un dispositif de vision bas niveau de lumière constitué d’un intensificateur de lumière (IL) couplé à une caméra numérique d’une part, et d’une caméra infrarouge (IR) d’autre part. L’objectif de cette thèse est d’améliorer ce dispositif en ciblant les défauts afin de les corriger.Une première partie consiste à réduire le bruit dont souffrent les images IL. Cela nécessite d’évaluer la nature du bruit qui corrompt ces images. Pour cela, une méthode d’estimation automatique du bruit est mise en place. L’estimation repose sur la détection non paramétrique de zones homogènes de l’image. Les statistiques du bruit peuvent être alors être estimées à partir de ces régions homogènes à l’aide d’une méthode d’estimation robuste de la fonction de niveau de bruit par minimisation l1.Grâce à l’estimation du bruit, les images IL peuvent alors débruitées. Nous avons pour cela développé dans la seconde partie un algorithme de débruitage d’images qui associe les moyennes non locales aux méthodes variationnelles en effectuant une régularisation adaptative pondérée parune attache aux données non locale. Une adaptation au débruitage de séquences d’images permet ensuite de tenir compte de la redondance d’information apportée par le flux vidéo, en garantissant stabilité temporelle et préservation des structures fines.Enfin, dans la troisième partie les informations issues des capteurs optique et infrarouge sont recalées dans un même référentiel. Nous proposons pour cela un critère de recalage multimodal basé sur l’alignement des contours des images. Combiné à une résolution par montée de gradient et à un schéma temporel, l’approche proposée permet de recaler de façon robuste les deuxmodalités, en vue d’une ultérieure fusion.Night vision for helicopter pilots is artificially enhanced by a night vision system. It consists in a light intensifier (LI) coupled with a numerical camera, and an infrared camera. The goal of this thesis is to improve this device by analyzing the defaults in order to correct them.The first part consists in reducing the noise level on the LI images. This requires to evaluate the nature of the noise corrupting these images, so an automatic noise estimation method has been developed. The estimation is based on a non parametric detection of homogeneous areas.Then the noise statistics are estimated using these homogeneous regions by performing a robust l`1 estimation of the noise level function.The LI images can then be denoised using the noise estimation. We have developed in the second part a denoising algorithm that combines the non local means with variational methods by applying an adaptive regularization weighted by a non local data fidelity term. Then this algorithm is adapted to video denoising using the redundancy provided by the sequences, hence guaranteeing temporel stability and preservation of the fine structures.Finally, in the third part data from the optical and infrared sensors are registered. We propose an edge based multimodal registration metric. Combined with a gradient ascent resolution and a temporel scheme, the proposed method allows robust registration of the two modalities for later fusion

Numerical night vision system : Automatic restoration and multimodal registration of low light level images

La vision de nuit des pilotes d’hélicoptère est artificiellement assistée par un dispositif de vision bas niveau de lumière constitué d’un intensificateur de lumière (IL) couplé à une caméra numérique d’une part, et d’une caméra infrarouge (IR) d’autre part. L’objectif de cette thèse est d’améliorer ce dispositif en ciblant les défauts afin de les corriger.Une première partie consiste à réduire le bruit dont souffrent les images IL. Cela nécessite d’évaluer la nature du bruit qui corrompt ces images. Pour cela, une méthode d’estimation automatique du bruit est mise en place. L’estimation repose sur la détection non paramétrique de zones homogènes de l’image. Les statistiques du bruit peuvent être alors être estimées à partir de ces régions homogènes à l’aide d’une méthode d’estimation robuste de la fonction de niveau de bruit par minimisation l1.Grâce à l’estimation du bruit, les images IL peuvent alors débruitées. Nous avons pour cela développé dans la seconde partie un algorithme de débruitage d’images qui associe les moyennes non locales aux méthodes variationnelles en effectuant une régularisation adaptative pondérée parune attache aux données non locale. Une adaptation au débruitage de séquences d’images permet ensuite de tenir compte de la redondance d’information apportée par le flux vidéo, en garantissant stabilité temporelle et préservation des structures fines.Enfin, dans la troisième partie les informations issues des capteurs optique et infrarouge sont recalées dans un même référentiel. Nous proposons pour cela un critère de recalage multimodal basé sur l’alignement des contours des images. Combiné à une résolution par montée de gradient et à un schéma temporel, l’approche proposée permet de recaler de façon robuste les deuxmodalités, en vue d’une ultérieure fusion.Night vision for helicopter pilots is artificially enhanced by a night vision system. It consists in a light intensifier (LI) coupled with a numerical camera, and an infrared camera. The goal of this thesis is to improve this device by analyzing the defaults in order to correct them.The first part consists in reducing the noise level on the LI images. This requires to evaluate the nature of the noise corrupting these images, so an automatic noise estimation method has been developed. The estimation is based on a non parametric detection of homogeneous areas.Then the noise statistics are estimated using these homogeneous regions by performing a robust l`1 estimation of the noise level function.The LI images can then be denoised using the noise estimation. We have developed in the second part a denoising algorithm that combines the non local means with variational methods by applying an adaptive regularization weighted by a non local data fidelity term. Then this algorithm is adapted to video denoising using the redundancy provided by the sequences, hence guaranteeing temporel stability and preservation of the fine structures.Finally, in the third part data from the optical and infrared sensors are registered. We propose an edge based multimodal registration metric. Combined with a gradient ascent resolution and a temporel scheme, the proposed method allows robust registration of the two modalities for later fusion

L’emprise du dépôt de tramway du Raincy

L’aspect le plus intéressant du dépôt de tramway du Raincy semble être, à bien des égards, celui des rapports dialectiques qu’entretiennent le développement urbain et celui des transports en commun. On évitera les aspects techniques abondamment traités par ailleurs. D’abord, les chemins de fer La voie ferrée guide la colonisation dans toute la région, où les lotissements s’organisent le long des lignes de banlieue. On comprend bien ainsi la volonté des élus locaux d’attirer la voie ferrée sur..