Les réseaux de capteurs sans fil d'images sont utilisés aujourd'hui dans de nombreuses applications qui diffèrent par leurs objectifs et leurs contraintes individuelles. Toutefois, le dénominateur commun de toutes les applications de réseaux de capteurs reste la vulnérabilité des noeuds-capteurs en raison de leurs ressources matérielles limitées dont la plus contraignante est l'énergie. En effet, les technologies sans fil disponibles dans ce type de réseaux sont généralement à faible portée, et les ressources matérielles (CPU, batterie) sont également de faible puissance. Il faut donc répondre à un double objectif : l'efficacité d'une solution tout en offrant une bonne qualité d'image à la réception. La contribution de cette thèse porte principalement sur l'étude des méthodes de traitement et de compression d'images au noeud-caméra, nous avons proposé une nouvelle méthode de compression d'images qui permet d'améliorer l'efficacité énergétique des réseaux de capteurs sans fil. Des expérimentations sur une plate-forme réelle de réseau de capteurs d'images ont été réalisées afin de démontrer la validité de nos propositions, en mesurant des aspects telles que la quantité de mémoire requise pour l'implantation logicielle de nos algorithmes, leur consommation d'énergie et leur temps d'exécution. Nous présentons aussi, les résultats de synthèse de la chaine de compression proposée sur des systèmes à puce FPGA et ASIC / The increasing development of Wireless Camera Sensor Networks today allows a wide variety of applications with different objectives and constraints. However, the common problem of all the applications of sensor networks remains the vulnerability of sensors nodes because of their limitation in material resources, the most restricting being energy. Indeed, the available wireless technologies in this type of networks are usually a low-power, short-range wireless technology and low power hardware resources (CPU, battery). So we should meet a twofold objective: an efficient solution while delivering outstanding image quality on reception. This thesis concentrates mainly on the study and evaluation of compression methods dedicated to transmission over wireless camera sensor networks. We have suggested a new image compression method which decreases the energy consumption of sensors and thus maintains a long network lifetime. We evaluate its hardware implementation using experiments on real camera sensor platforms in order to show the validity of our propositions, by measuring aspects such as the quantity of memory required for the implantation program of our algorithms, the energy consumption and the execution time. We then focus on the study of the hardware features of our proposed method of synthesis of the compression circuit when implemented on a FPGA and ASIC chip prototype

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Thesis (DSc (Mathematical Sciences. Applied Mathematics))--University of Stellenbosch, 2009. / The replacement of the standard discrete cosine transform (DCT) of JPEG with the windowed modifed DCT (MDCT) is investigated to determine whether improvements in numerical quality can be achieved. To this end, we employ an existing algorithm for optimal quantisation, for which we also propose improvements. This involves the modelling and prediction of quantisation tables to initialise the algorithm, a strategy that is also thoroughly tested. Furthermore, the effects of various window functions on the coding results are investigated, and we find that improved quality can indeed be achieved by modifying JPEG in this fashion.

This thesis deals with the development and evaluation of blind discrete cosine transform-based watermarking algorithms for copyright protection of digital still images using handwritten signatures and mobile phone numbers. The new algorithms take into account the perceptual capacity of each low frequency coefficients inside the Discrete Cosine Transform (DCT) blocks before embedding the watermark information. They are suitable for grey-scale and colour images. Handwritten signatures are used instead of pseudo random numbers. The watermark is inserted in the green channel of the RGB colour images and the luminance channel of the YCrCb images. Mobile phone numbers are used as watermarks for images captured by mobile phone cameras. The information is embedded multiple-times and a shuffling scheme is applied to ensure that no spatial correlation exists between the original host image and the multiple watermark copies. Multiple embedding will increase the robustness of the watermark against attacks since each watermark will be individually reconstructed and verified before applying an averaging process. The averaging process has managed to reduce the amount of errors of the extracted information. The developed watermarking methods are shown to be robust against JPEG compression, removal attack, additive noise, cropping, scaling, small degrees of rotation, affine, contrast enhancements, low-pass, median filtering and Stirmark attacks. The algorithms have been examined using a library of approximately 40 colour images of size 512 512 with 24 bits per pixel and their grey-scale versions. Several evaluation techniques were used in the experiment with different watermarking strengths and different signature sizes. These include the peak signal to noise ratio, normalized correlation and structural similarity index measurements. The performance of the proposed algorithms has been compared to other algorithms and better invisibility qualities with stronger robustness have been achieved.

Cette thèse s’inscrit dans la recherche d’images basée sur leur contenu. La recherche opère sur des images eprésentéesdans un domaine transformé et où sont construits directement les vecteurs de caractéristiques ou indices. Deux types detransformations sont explorés : la transformée en cosinus discrète ou Discrete Cosine Transform (DCT) et la transforméen ondelettes discrète ou Discrete Wavelet Transform (DWT), utilisés dans les normes de compression JPEG et JPEG2000. Basés sur les propriétés des coefficients de la transformation, différents vecteurs de caractéristiquessont proposés. Ces vecteurs sont mis en oeuvre dans la reconnaissance de visages et de textures couleur.Dans le domaine DCT, sont proposés quatre types de vecteurs de caractéristiques dénommés «patterns» : Zigzag-Pattern,Sum-Pattern, Texture-Pattern et Color-Pattern. Le premier type est l’amélioration d’une approche existante. Les trois derniers intègrent la capacité de compactage des coefficients DCT, sachant que certains coefficients représentent une information de directionnalité. L’histogramme de ces vecteurs est retenu comme descripteur de l’image. Pour une réduction de la dimension du descripteur lors de la construction de l’histogramme il est défini, soit une adjacence sur des patterns proches puis leur fusion, soit une sélection des patterns les plus fréquents. Ces approches sont évaluées sur des bases de données d’images de visages ou de textures couramment utilisées. Dans le domaine DWT, deux types d’approches sont proposés. Dans le premier, un vecteur-couleur et un vecteur–texture multirésolution sont élaborés. Cette approche se classe dans le cadre d’une caractérisation séparée de la couleur et de la texture. La seconde approche se situe dans le contexte d’une caractérisation conjointe de la couleur et de la texture. Comme précédemment, l’histogramme des vecteurs est choisi comme descripteur en utilisant l’algorithme K-means pour construire l’histogramme à partir de deux méthodes. La première est le procédé classique de regroupement des vecteurs par partition. La seconde est un histogramme basé sur une représentation parcimonieuse dans laquelle la valeur des bins représente le poids total des vecteurs de base de la représentation. / This thesis comes within content-based image retrieval for images by constructing feature vectors directly fromtransform domain. In particular, two kinds of transforms are concerned: Discrete Cosine Transform (DCT) andDiscrete Wavelet Transform (DWT), which are used in JPEG and JPEG2000 compression standards. Based onthe properties of transform coefficients, various feature vectors in DCT domain and DWT domain are proposedand applied in face recognition and color texture retrieval. The thesis proposes four kinds of feature vectors in DCTdomain: Zigzag-Pattern, Sum-Pattern, Texture-Pattern and Color-Pattern. The first one is an improved method based onan existing approach. The last three ones are based on the capability of DCT coefficients for compacting energy and thefact that some coefficients hold the directional information of images. The histogram of these patterns is chosen as descriptor of images. While constructing the histogram, with the objective to reduce the dimension of the descriptor, either adjacent patterns are defined and merged or a selection of the more frequent patterns is done. These approaches are evaluated on widely used face databases and texture databases. In the aspect of DWT domain, two kinds of approaches for color texture retrieval are proposed. In the first one, color-vector and multiresolution texture-vector are constructed, which categorize this approach into the context of extracting color and texture features separately. In contrast, the second approachis in the context of extracting color and texture features jointly: multiresolution feature vectors are extracted from luminance and chrominance components of color texture. Histogram of vectors is again chosen as descriptor and using k-means algorithm to divide feature vectors into partitions corresponding to the bins of histogram. For histogram generation, two methods are used. The first one is the classical method, in which the number of vectors that fall into the corresponding partition is counted. The second one is the proposition of a sparse representation based histogram in which a bin value represents the total weight of corresponding basis vector in the sparse representation.

<p>At Saab Aerosystems, situated in Linköping Sweden, there is a presentation and manoeuvre simulator simulating the fighter jet JAS-39 Gripen. This flight simulator is called PMSIM. In this thesis we study how to transfer sensor images generated by PMSIM to other simulators or desktop computers. The transmission is band-limited so some kind of image coding must be used. Because of this the greater part of this thesis is concerned with image coding. </p><p>To fulfill the real time requirement the image coding has to be quite simple and the transmission has to be fast. To achieve fast transmission the network protocol has to use as little overhead information as possible. Such a protocol has therefore been designed and implemented. </p><p>This report also includes a survey about real radio links. This survey investigates how the quality of the video stream can be affected by noise and other disturbing elements. </p><p>The work in this report revolves around the implementation of a video link. The purpose of this link is to transmit and display sensor images. The link consists mainly of the three following parts: image coder, network link and image player. The image coding has been focused on MPEG and wavelets. </p><p>The wavelet technique is not a well known coding principle for video applications. Although as a coding technique for still images the technique is well known. For instance it is used in the JPEG2000-standard. Experiments conducted and published in this report suggest that for some applications the wavelet technique can be a viable candidate, with respect to the MPEG technique, for a video coder.</p>

At Saab Aerosystems, situated in Linköping Sweden, there is a presentation and manoeuvre simulator simulating the fighter jet JAS-39 Gripen. This flight simulator is called PMSIM. In this thesis we study how to transfer sensor images generated by PMSIM to other simulators or desktop computers. The transmission is band-limited so some kind of image coding must be used. Because of this the greater part of this thesis is concerned with image coding. To fulfill the real time requirement the image coding has to be quite simple and the transmission has to be fast. To achieve fast transmission the network protocol has to use as little overhead information as possible. Such a protocol has therefore been designed and implemented. This report also includes a survey about real radio links. This survey investigates how the quality of the video stream can be affected by noise and other disturbing elements. The work in this report revolves around the implementation of a video link. The purpose of this link is to transmit and display sensor images. The link consists mainly of the three following parts: image coder, network link and image player. The image coding has been focused on MPEG and wavelets. The wavelet technique is not a well known coding principle for video applications. Although as a coding technique for still images the technique is well known. For instance it is used in the JPEG2000-standard. Experiments conducted and published in this report suggest that for some applications the wavelet technique can be a viable candidate, with respect to the MPEG technique, for a video coder.

Many scientific data sets are contaminated by noise, either because of data acquisition process, or because of naturally occurring phenomena. A first step in analyzing such data sets is denoising, i.e., removing additive noise from a noisy image. For images, noise suppression is a delicate and a difficult task. A trade of between noise reduction and the preservation of actual image features has to be made in a way that enhances the relevant image content. The beginning chapter in this thesis is introductory in nature and discusses the Popular denoising techniques in spatial and frequency domains. Wavelet transform has wide applications in image processing especially in denoising of images. Wavelet systems are a set of building blocks that represent a signal in an expansion set involving indices for time and scale. These systems allow the multi-resolution representation of signals. Several well known denoising algorithms exist in wavelet domain which penalize the noisy coefficients by threshold them. We discuss the wavelet transform based denoising of images using bit planes. This approach preserves the edges in an image. The proposed approach relies on the fact that wavelet transform allows the denoising strategy to adapt itself according to directional features of coefficients in respective sub-bands. Further, issues related to low complexity implementation of this algorithm are discussed. The proposed approach has been tested on different sets images under different noise intensities. Studies have shown that this approach provides a significant reduction in normalized mean square error (NMSE). The denoised images are visually pleasing. Many of the image compression techniques still use the redundancy reduction property of the discrete cosine transform (DCT). So, the development of a denoising algorithm in DCT domain has a practical significance. In chapter 3, a DCT based denoising algorithm is presented. In general, the design of filters largely depends on the a-priori knowledge about the type of noise corrupting the image and image features. This makes the standard filters to be application and image specific. The most popular filters such as average, Gaussian and Wiener reduce noisy artifacts by smoothing. However, this operation normally results in smoothing of the edges as well. On the other hand, sharpening filters enhance the high frequency details making the image non-smooth. An integrated approach to design filters based on DCT is proposed in chapter 3. This algorithm reorganizes DCT coefficients in a wavelet transform manner to get the better energy clustering at desired spatial locations. An adaptive threshold is chosen because such adaptively can improve the wavelet threshold performance as it allows additional local information of the image to be incorporated in the algorithm. Evaluation results show that the proposed filter is robust under various noise distributions and does not require any a-priori Knowledge about the image. Inpainting is another application that comes under the category of image processing. In painting provides a way for reconstruction of small damaged portions of an image. Filling-in missing data in digital images has a number of applications such as, image coding and wireless image transmission for recovering lost blocks, special effects (e.g., removal of objects) and image restoration (e.g., removal of solid lines, scratches and noise removal). In chapter 4, a wavelet based in painting algorithm is presented for reconstruction of small missing and damaged portion of an image while preserving the overall image quality. This approach exploits the directional features that exist in wavelet coefficients in respective sub-bands. The concluding chapter presents a brief review of the three new approaches: wavelet and DCT based denoising schemes and wavelet based inpainting method.

En dépit du succès que les implantations optiques des applications de traitement d'images ont connu, le traitement optique de l'information suscite aujourd'hui moins d'intérêt que dans les années 80-90. Ceci est dû à l'encombrement des réalisations optiques, la qualité des images traitées et le coût des composants optiques. De plus, les réalisations optiques ont eu du mal à s'affranchir de l'avènement des circuits numériques. C'est dans ce cadre que s'inscrivent les travaux de cette thèse dont l'objectif est de proposer une implantation numérique des méthodes optiques de traitement d'images. Pour réaliser cette implantation nous avons choisi d'utiliser les FPGA et les GPU grâce aux bonnes performances de ces circuits en termes de rapidité. En outre, pour améliorer la productivité nous nous sommes focalisés à la réutilisation des blocs préconçus ou IP " Intellectual Properties ". Malgré que les IP commerciales existantes soient optimisées, ces dernières sont souvent payantes et dépendent de la famille de la carte utilisée. La première contribution est de proposer une implantation optimisée des IP pour le calcul de la transformée de Fourier FFT et de la DCT. En effet, le choix de ces deux transformations est justifié par l'utilisation massive de ces deux transformées (FFT et DCT), dans les algorithmes de reconnaissance de formes et de compression, respectivement. La deuxième contribution est de valider le fonctionnement des IP proposées par un banc de test et de mesure. Enfin, la troisième contribution est de concevoir sur FPGA et GPU des implantations numériques des applications de reconnaissance de formes et de compression. Un des résultats probant obtenu dans cette thèse consiste à avoir une rapidité de l'IP FFT proposée 3 fois meilleure que celle de l'IP FFT Xilinx et de pouvoir réaliser 4700 corrélations par seconde.

Face recognition can be used in various biometric applications ranging from identifying criminals entering an airport to identifying an unconscious patient in the hospital With the introduction of 3-dimensional scanners in the last decade, researchers have begun to develop new methods for 3-D face recognition. This thesis focuses on 3-D face recognition using the one- and two-dimensional Discrete Cosine Transform (DCT) . A feature ranking based dimensionality reduction strategy is introduced to select the DCT coefficients that yield the best classification accuracies. Two forms of 3-D representation are used: point cloud and depth map images. These representations are extracted from the original VRML files in a face database and are normalized during the extraction process. Classification accuracies exceeding 97% are obtained using the point cloud images in conjunction with the 2-D DCT.