Descripteur
Termes IGN > mathématiques > analyse numérique > optimisation (mathématiques)
optimisation (mathématiques)Synonyme(s)algorithme d'optimisation minimisationVoir aussi |
Documents disponibles dans cette catégorie (451)
Ajouter le résultat dans votre panier
Visionner les documents numériques
Affiner la recherche Interroger des sources externes
Etendre la recherche sur niveau(x) vers le bas
Sparse signal modeling: Application to image compression, Image error concealment and compressed sensing / Ali Akbari (2018)
Titre : Sparse signal modeling: Application to image compression, Image error concealment and compressed sensing Type de document : Thèse/HDR Auteurs : Ali Akbari, Auteur Editeur : Paris : Sorbonne Université Année de publication : 2018 Importance : 158 p. Format : 21 x 30 cm Note générale : bibliographie
Thèse de Doctorat de Traitement du signal et de l’image, Sorbonne UniversitéLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement du signal
[Termes IGN] acquisition comprimée
[Termes IGN] compensation
[Termes IGN] compression d'image
[Termes IGN] modélisation
[Termes IGN] problème inverse
[Termes IGN] reconstruction d'image
[Termes IGN] représentation parcimonieuse
[Termes IGN] théorie du signalIndex. décimale : THESE Thèses et HDR Résumé : (auteur) Signal models are a cornerstone of contemporary signal and image processing methodology. In this report, two particular signal modeling methods, called analysis and synthesis sparse representation, are studied which have been proven to be effective for many signals, such as natural images, and successfully used in a wide range of applications. Both models represent signals in terms of linear combinations of an underlying set, called dictionary, of elementary signals known as atoms. The driving force behind both models is sparsity of the representation coefficients, i.e. the rapid decay of the representation coefficients over the dictionary. On the other hands, the dictionary choice determines the success of the entire model. According to these two signal models, there have been two main disciplines of dictionary designing; harmonic analysis approach and machine learning methodology. The former leads to designing the dictionaries with easy and fast implementation, while the latter provides a simple and expressive structure for designing adaptable and efficient dictionaries. The main goal of this thesis is to provide new applications to these signal modeling methods by addressing several problems from various perspectives. It begins with the direct application of the sparse representation, i.e. image compression. The line of research followed in this area is the synthesis-based sparse representation approach in the sense that the dictionary is not fixed and predefined, but learned from training data and adapted to data, yielding a more compact representation. A new Image codec based on adaptive sparse representation over a trained dictionary is proposed, wherein different sparsity levels are assigned to the image patches belonging to the salient regions, being more conspicuous to the human visual system. Experimental results show that the proposed method outperforms the existing image coding standards, such as JPEG and JPEG2000, which use an analytic dictionary, as well as the state-of-the-art codecs based on the trained dictionaries. In the next part of thesis, it focuses on another important application of the sparse signal modeling, i.e. solving inverse problems, especially for error concealment (EC), wherein a corrupted image is reconstructed from the incomplete data, and Compressed Sensing recover, where an image is reconstructed from a limited number of random measurements. Signal modeling is usually used as a prior knowledge about the signal to solve these NP-hard problems. In this thesis, inspired by the analysis and synthesis sparse models, these challenges are transferred into two distinct sparse recovery frameworks and several recovery methods are proposed. Compared with the state-of-the-art EC and CS algorithms, experimental results show that the proposed methods show better reconstruction performance in terms of objective and subjective evaluations. This thesis is finalized by giving some conclusions and introducing some lines for future works. Note de contenu : 1- Introduction
2- Sparsity-based signal models
3- Image compressed sensing recovery
4- Receiver-based error concealment based on synthesis sparse recovery
5- Transmitter-based error concealment based on sparse recovery
6- Sparse representation-based image compression
7- Conclusion and future directionsNuméro de notice : 25937 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse française Note de thèse : Thèse de Doctorat : Spécialité : Traitement du signal et de l’image : Paris : 2018 nature-HAL : Thèse DOI : sans En ligne : http://www.theses.fr/2018SORUS461 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96286 Traitement et analyse des contraintes urbaines pour une optimisation morphologique : Etude comparative des modèles MorVer et SimPLU3D / Alia Belkaid (2018)
Titre : Traitement et analyse des contraintes urbaines pour une optimisation morphologique : Etude comparative des modèles MorVer et SimPLU3D Type de document : Article/Communication Auteurs : Alia Belkaid, Auteur ; Mickaël Brasebin , Auteur ; Ines Hassoumi, Auteur Editeur : [s.l.] : [s.n.] Année de publication : 2018 Conférence : TAIMA 2018, Traitement et Analyse de l'Information Méthodes et Applications 30/04/2018 05/05/2018 Hammamet Tunisie Note générale : bibliographie Langues : Français (fre) Descripteur : [Termes IGN] analyse spatiale
[Termes IGN] morphologie urbaine
[Termes IGN] optimisation (mathématiques)
[Termes IGN] programmation par contraintes
[Termes IGN] règlement
[Termes IGN] volume (grandeur)
[Termes IGN] zone urbaine
[Vedettes matières IGN] GéovisualisationRésumé : (auteur) La morphologie urbaine est régulée par des règlements locaux d’urbanisme qui s’expriment à travers des textes. L’objectif de cet article est : i) de comparer deux modèles, SimPLU3D et MorVeR, qui traduisent les contraintes urbaines morphologiques en volumes, ii) et de relever les potentialités et les limites des deux approches informatiques. La mise en rapport des règles urbaines avec le volume contraint permet de distinguer le volume constructible optimal « géométriquement » du volume réglementaire qui optimise au mieux les contraintes urbaines.
Urban morphology is controlled by local planning regulations that are expressed through legal texts. The objective of this article is to compare two models, SimPLU3D and MorVeR, which transform the urban morphological constraints into volumes and to meet the potential and limitations of both computational approaches. The relation between the urban rules with the authorized volume leads to the optimal building volume "geometrically" regulatory volume which better optimizes the urban constraints.Numéro de notice : C2018-025 Affiliation des auteurs : LASTIG COGIT+Ext (2012-2019) Thématique : GEOMATIQUE/URBANISME Nature : Poster nature-HAL : Poster-avec-CL DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90492 Documents numériques
en open access
Traitement et analyse des contraintes urbaines ... - posterImage Jpeg Hybrid image noise reduction algorithm based on genetic ant colony and PCNN / Chong Shen in The Visual Computer, vol 33 n° 11 (November 2017)
[article]
Titre : Hybrid image noise reduction algorithm based on genetic ant colony and PCNN Type de document : Article/Communication Auteurs : Chong Shen, Auteur ; Ding Wang, Auteur ; Shuming Tang, Auteur ; Huiliang Cao, Auteur ; Jun Liu, Auteur Année de publication : 2017 Article en page(s) : pp 1373 - 1384 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] algorithme génétique
[Termes IGN] filtrage du bruit
[Termes IGN] optimisation par colonie de fourmis
[Termes IGN] réseau neuronal artificielRésumé : (Auteur) Pulse Coupled Neural Network (PCNN) has gained widespread attention as a nonlinear filtering technology in reducing the noise while keeping the details of images well, but how to determine the proper parameters for PCNN is a big challenge. In this paper, a method that can optimize the parameters of PCNN by combining the genetic algorithm (GA) and ant colony algorithm is proposed, which named as GACA, and the optimized procedure is named as GACA-PCNN. Firstly, the noisy image is filtered by median filter in the proposed GACA-PCNN method; then, the noisy image is filtered by GACA-PCNN constantly and the median filtering image is used as a reference image; finally, a set of parameters of PCNN can be automatically estimated by GACA, and the pretty effective denoising image will be obtained. Experimental results indicate that GACA-PCNN has a better performance on PSNR (peak signal noise rate) and a stronger capacity of preserving the details than previous denoising techniques. Numéro de notice : A2017-712 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Article DOI : 10.1007/s00371-016-1325-x En ligne : https://doi.org/10.1007/s00371-016-1325-x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=88093
in The Visual Computer > vol 33 n° 11 (November 2017) . - pp 1373 - 1384[article]Robust minimum volume simplex analysis for hyperspectral unmixing / Shaoquan Zhang in IEEE Transactions on geoscience and remote sensing, vol 55 n° 11 (November 2017)
[article]
Titre : Robust minimum volume simplex analysis for hyperspectral unmixing Type de document : Article/Communication Auteurs : Shaoquan Zhang, Auteur ; Alexander Agathos, Auteur ; Jun Li, Auteur Année de publication : 2017 Article en page(s) : pp 6431 - 6439 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] algorithme du simplexe
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] factorisation
[Termes IGN] image hyperspectrale
[Termes IGN] méthode robusteRésumé : (Auteur) Most blind hyperspectral unmixing methods exploit convex geometry properties of hyperspectral data. The minimum volume simplex analysis (MVSA) is one of such methods, which, as many others, estimates the minimum volume (MV) simplex where the measured vectors live. MVSA was conceived to circumvent the matrix factorization step often implemented by MV-based algorithms and also to cope with outliers, which compromise the results produced by MV algorithms. Inspired by the recently proposed robust MV enclosing simplex (RMVES) algorithm, we herein introduce the robust MVSA (RMVSA), which is a version of MVSA robust to noise. As in RMVES, the robustness is achieved by employing chance constraints, which control the volume of the resulting simplex. RMVSA differs, however, substantially from RMVES in the way optimization is carried out. In this paper, we develop a linearization relaxation of the nonlinear chance constraints, which can greatly lighten the computational complex of chance constraint problems. The effectiveness of RMVSA is illustrated by comparing its performance with the state of the art. Numéro de notice : A2017-749 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2017.2728104 En ligne : https://doi.org/10.1109/TGRS.2017.2728104 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=88784
in IEEE Transactions on geoscience and remote sensing > vol 55 n° 11 (November 2017) . - pp 6431 - 6439[article]Spatial group sparsity regularized nonnegative matrix factorization for hyperspectral unmixing / Xinyu Wang in IEEE Transactions on geoscience and remote sensing, vol 55 n° 11 (November 2017)
[article]
Titre : Spatial group sparsity regularized nonnegative matrix factorization for hyperspectral unmixing Type de document : Article/Communication Auteurs : Xinyu Wang, Auteur ; Yanfei Zhong, Auteur ; Liangpei Zhang, Auteur ; Yanyan Xu, Auteur Année de publication : 2017 Article en page(s) : pp 6287 - 6304 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] factorisation de matrice non-négative
[Termes IGN] image hyperspectrale
[Termes IGN] optimisation (mathématiques)
[Termes IGN] segmentation d'imageRésumé : (Auteur) In recent years, blind source separation (BSS) has received much attention in the hyperspectral unmixing field due to the fact that it allows the simultaneous estimation of both endmembers and fractional abundances. Although great performances can be obtained by the BSS-based unmixing methods, the decomposition results are still unstable and sensitive to noise. Motivated by the first law of geography, some recent studies have revealed that spatial information can lead to an improvement in the decomposition stability. In this paper, the group-structured prior information of hyperspectral images is incorporated into the nonnegative matrix factorization optimization, where the data are organized into spatial groups. Pixels within a local spatial group are expected to share the same sparse structure in the low-rank matrix (abundance). To fully exploit the group structure, image segmentation is introduced to generate the spatial groups. Instead of a predefined group with a regular shape (e.g., a cross or a square window), the spatial groups are adaptively represented by superpixels. Moreover, the spatial group structure and sparsity of the abundance are integrated as a modified mixed-norm regularization to exploit the shared sparse pattern, and to avoid the loss of spatial details within a spatial group. The experimental results obtained with both simulated and real hyperspectral data confirm the high efficiency and precision of the proposed algorithm. Numéro de notice : A2017-747 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2017.2724944 En ligne : https://doi.org/10.1109/TGRS.2017.2724944 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=88782
in IEEE Transactions on geoscience and remote sensing > vol 55 n° 11 (November 2017) . - pp 6287 - 6304[article]The Naïve Overfitting Index Selection (NOIS): A new method to optimize model complexity for hyperspectral data / Alby D. Rocha in ISPRS Journal of photogrammetry and remote sensing, vol 133 (November 2017)PermalinkA structured regularization framework for spatially smoothing semantic labelings of 3D point clouds / Loïc Landrieu in ISPRS Journal of photogrammetry and remote sensing, vol 132 (October 2017)PermalinkA GPU-accelerated adaptive kernel density estimation approach for efficient point pattern analysis on spatial big data / Guiming Zhang in International journal of geographical information science IJGIS, vol 31 n° 9-10 (September - October 2017)PermalinkPoint cloud refinement with self-calibration of a mobile multibeam lidar sensor / Houssem Nouira in Photogrammetric record, vol 32 n° 159 (September 2017)PermalinkSDE: A novel selective, discriminative and equalizing feature representation for visual recognition / Guo-Sen Xie in International journal of computer vision, vol 124 n° 2 (1 September 2017)PermalinkMulti-view performance capture of surface details / Nadia Robertini in International journal of computer vision, vol 124 n° 1 (August 2017)PermalinkA novel preunmixing framework for efficient detection of linear mixtures in hyperspectral images / Andrea Marinoni in IEEE Transactions on geoscience and remote sensing, vol 55 n° 8 (August 2017)PermalinkGold – A novel deconvolution algorithm with optimization for waveform LiDAR processing / Tan Zhou in ISPRS Journal of photogrammetry and remote sensing, vol 129 (July 2017)Permalink3D tree modeling from incomplete point clouds via optimization and L1-MST / Jie Mei in International journal of geographical information science IJGIS, vol 31 n° 5-6 (May-June 2017)PermalinkApplying detection proposals to visual tracking for scale and aspect ratio adaptability / Dafei Huang in International journal of computer vision, vol 122 n° 3 (May 2017)Permalink