Le test de production des imageurs CMOS est une étape clé du flot de fabrication afin de garantir des produits répondant aux critères de qualité et exempts de défauts de fabrication. Ces tests sont classifiés en test électrique et test optique. Le test électrique est basé sur du test structurel qui vérifie la partie numérique et certain blocks analogiques. La plus grande partie des circuits analogiques et la matrice des capteurs sont testés par le test optique. Ce test est basé sur des captures d'images et sur une recherche des défauts au moyen d'algorithmes de calcul spécifiques appliqué sur les images. Proche du fonctionnement applicatif, ils sont qualifies de test fonctionnels. La couverture des défauts obtenue par les tests de type fonctionnel est généralement inférieure à celle obtenue par un test structurel. L'objectif de cette thèse est d'étudier et développer des solutions de test alternatives aux tests fonctionnels afin d'obtenir des meilleurs taux de couverture de défauts, améliorant ainsi la fiabilité, tout en réduisant le temps de test et son coût. Parmi les défauts optiques qui ont causé des retours client par le passés, le défaut qui présent Horizontal Fixed Pattern Noise (HFPN) donnent lieu à un taux de couverture insuffisant. Ces recherches ont été orientées vers l'amélioration du taux de couverture de défauts dite de HFPN dans le test de production des imageurs CMOS.Le HFPN est défini comme une sorte d'image défaillante qui présente sous la forme des bandes résiduelles horizontales. Il est principalement causé par les défauts dans les lignes d'interconnexion qui alimentent et pilotent les pixels. La détection d'un défaut HFPN dans les tests optiques actuels est par comparer les valeurs moyennes de chaque ligne de pixels avec les lignes adjacentes. Si la différence d'une ligne par rapport aux lignes adjacentes est supérieur à la limites spécifié, la ligne est constaté comme défectueuse. Cette limite est donc difficile d'être ajusté face à un compromis entre le taux de couverture de ce défaut et le rendement.Dans cette thèse, nous avons proposé d'abord une amélioration de l'algorithme de détection pour améliorer le test optique actuelle. L'amélioration de test optique est validée par des résultats de test en production en appliquant le nouvel algorithme. Par la suite, une technique d'auto test (BIST) pour la détection des défauts dans les lignes d'interconnexion de matrice des pixels est étudiée et évalué. Enfin, une puce imageur avec le technique d'auto test embarqué est conçu et fabriqué pour la validation expérimentale. / Current production testing of CMOS imager sensors is mainly based on capturing images and detecting failures by image processing with special algorithms. The fault coverage of this costly optical test is not sufficient given the quality requirements. Studies on devices produced at large volume have shown that Horizontal Fixed Pattern Noise (HFPN) is one of the common image failures encountered on products that present fault coverage problems, and this is the main cause of customer returns for many products. A detailed analysis of failed devices has demonstrated that HFPN failures arise from changes of electronic circuit topology in pixel addressing decoders or the metal lines required for pixel powering and control. These changes are usually due to the presence of spot defects, causing some pixels in a row to operate incorrectly, leading to an HFPN failure. Moreover, defects resulting in partially degraded metal lines may not induce image failure in limited industrial test conditions, passing the optical tests. Later, these defects may produce an image failure in the field, either because the capture conditions would be more stringent, or because the defects would evolve into catastrophic faults due to electromigration. In this paper, we have first enhanced the HFPN detection algorithm in order to improve the fault coverage of the optical test. Next, a built-in self-test structure is presented for the on-chip detection of catastrophic and non-catastrophic defects in the pixel power and control lines.

Submitted by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2016-11-25T15:39:21Z No. of bitstreams: 1 Dissertação - Ewerton G. Oliveira.pdf: 6135162 bytes, checksum: 3a074865f59774e056e5a06dd0c49501 (MD5) / Approved for entry into archive by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2016-11-25T15:39:37Z (GMT) No. of bitstreams: 1 Dissertação - Ewerton G. Oliveira.pdf: 6135162 bytes, checksum: 3a074865f59774e056e5a06dd0c49501 (MD5) / Approved for entry into archive by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2016-11-25T15:39:56Z (GMT) No. of bitstreams: 1 Dissertação - Ewerton G. Oliveira.pdf: 6135162 bytes, checksum: 3a074865f59774e056e5a06dd0c49501 (MD5) / Made available in DSpace on 2016-11-25T15:39:56Z (GMT). No. of bitstreams: 1 Dissertação - Ewerton G. Oliveira.pdf: 6135162 bytes, checksum: 3a074865f59774e056e5a06dd0c49501 (MD5) Previous issue date: 2016-04-18 / This work presents a study on the behavior and effectiveness of different Fixed-Pattern Noise (FPN) reduction techniques applied to different pixel topologies operating in logarithmic mode. The purpose of such study is the establishment of a consistent way to perform fair cross comparison of the effectiveness of different FPN attenuation techniques applied to pixels with different topologies and designed in the same technological node, and thus establish judgment criteria for determining which topology will be most suitable for implementation of an image sensor operating in logarithimic mode. Investigations of the effectiveness of two similar FPN reduction techniques applied to four different pixel topologies were performed through Monte Carlo simulations. The analyses of results of output signal swing, total and residual FPN, signal-to-distortion ratio, power consumption and fill factor are able to demonstrate which pixel topologies yield better results in each of these criteria. Such results provide valuable data that allows a more concise decision on which pixel topology and FPN reduction technique to choose in the design of an imager array with wide dynamic range. / Este trabalho apresenta um estudo sobre o comportamento e eficácia de diferentes técnicas de redução de ruído de padrão fixo, do inglês fixed-pattern noise (FPN), aplicadas a diferentes topologias de pixel operando em modo logarítmico. A finalidade deste estudo é o estabelecimento de um meio consistente para realizar comparação cruzada imparcial da eficácia de diferentes técnicas de redução de FPN aplicadas a pixeis com diferentes topologias e projetados sob o mesmo rótulo tecnológico, e assim estabelecer critérios de julgamento que permitam determinar qual topologia será a mais adequada para implementação de um sensor de imagem operando em modo logarítmico. Investigações da eficácia de duas técnicas de redução de FPN similares aplicadas a quatro diferentes topologias de pixel foram realizadas através de simulações Monte Carlo. As análises dos resultados de excursão do sinal de saída, FPN total e residual, razão de distorção do sinal, consumo de energia e fator de preenchimento são capazes de demonstrar que topologias de pixel produzem melhores resultados em cada um destes critérios. Tais resultados proporcionam dados valiosos que permitem uma mais concisa decisão sobre qual topologia de pixel e técnica de redução de FPN escolher no projeto de um sensor de imagem com largo alcance dinâmico.

Biologically inspired logarithmic CMOS sensors offer high dynamic range imaging capabilities without the difficulties faced by linear imagers. By compressing dynamic range while encoding contrast information, they mimic the human visual system’s response to photo stimuli in fewer bits than those used in linear sensors. Despite this prospect, logarithmic sensors suffer poor image quality due to illumination dependent fixed pattern noise (FPN), making individual pixels appear up to 100 times brighter or darker. This thesis is primarily concerned with alleviating FPN in logarithmic imagers in a simple and convenient way while undertaking a system approach to its origin, distribution and effect on the quality of monochrome and colour images, after FPN correction. Using the properties of the Human visual system, I propose to characterise the errors arising from FPN in a perceptually significant manner by proposing an error measure, never used before. Logarithmic operation over a wide dynamic range is first characterised using a new model; yi j =aj +bj ln(exp sqrt(cj +djxi)−1), where yi j is the response of the sensor to a light stimulus xi and aj, bj, cj and dj are pixel dependent parameters. Using a proposed correction procedure, pixel data from a monochromatic sensor array is FPN corrected to approximately 4% error over 5 decades of illumination even after digitisation - accuracy equivalent to four times the human eyes ability to just notice an illumination difference against a uniform background. By evaluating how error affects colour, the possibility of indiscernible residual colour error after FPN correction, is analytically explored using a standard set of munsell colours. After simulating the simple FPN correction procedure, colour quality is analysed using a Delta E76 perceptual metric, to check for perceptual discrepancies in image colour. It is shown that, after quantisation, the FPN correction process yields 1−2 Delta E76 error units over approximately 5 decades of illumination; colour quality being imperceptibly uniform in this range. Finally, tone-mapping techniques, required to compress high dynamic range images onto the low range of standard screens, have a predominantly logarithmic operation during brightness compression. A new Logr'Gb' colour representation is presented in this thesis, significantly reducing computational complexity, while encoding contrast information. Using a well-known tone mapping technique, images represented in this new format are shown to maintain colour accuracy when the green colour channel is compressed to the standard display range, instead of the traditional luminance channel. The trade off between colour accuracy and computation in this tone mapping approach is also demonstrated, offering a low cost alternative for applications with low display specifications.

Cette thèse apporte des solutions théoriques et pratiques à deux problèmes soulevés par la photographie numérique en présence de mouvement, et par la photographie infrarouge. La photographie d'objets en mouvement semblait ne pouvoir se faire qu'avec des temps d'exposition très courts, jusqu'à ce que deux travaux révolutionnaires proposent deux nouveaux types de caméra permettant un temps d'exposition arbitraire. Le flutter shutter de Agrawal et al. crée en effet un flou inversible, grâce à un obturateur aux séquences d'ouverture-fermeture bie{\it n choisies. Le motion invariant photography de Levin et al. obtient ce même effet avec une accélération constante de la caméra. Les deux méthodes suivent ainsi un nouveau paradigme, la computational photography, selon lequel les caméras sont repensées, car elles incluent un traitement numérique sophistiqué. Cette thèse propose une méthode pour évaluer la qualité image des nouvelles caméras. Le fil conducteur de l'analyse est donc l'évaluation du SNR (signal to noise ratio) de l'image obtenue après déconvolution. La théorie fournit des formules explicites pour le SNR, soulève deux paradoxes de ces caméras, et les résout. Elle permet d'obtenir le modèle de mouvement sous-jacent à chaque flutter shutter, notamment tous ceux qui sont brevetés. Une seconde partie plus brève aborde le problème de qualité principal en imagerie vidéo infrarouge, la non-uniformité. Il s'agit d'un bruit évolutif et structuré en colonnes causé par le capteur. La conclusion des travaux est qu'il est non seulement possible mais également efficace et robuste d'effectuer la correction sur une seule image. Cela permet de contourner le problème récurrent des "ghost artifacts"résultant d'une incohérence du traitement par rapport au modèle d'acquisition. / This thesis provides theoretical and practical solutions to two problems raised by digital photography of moving scenes, and infrared photography. Until recently photographing moving objects could only be done using short exposure times. Yet, two recent groundbreaking works have proposed two new designs of camera allowing arbitrary exposure times. The flutter shutter of Agrawal et al. creates an invertible motion blur by using a clever shutter technique to interrupt the photon flux during the exposure time according to a well chosen binary sequence. The motion-invariant photography of Levin et al. gets the same result by accelerating the camera at a constant rate. Both methods follow computational photography as a new paradigm. The conception of cameras is rethought to include sophisticated digital processing. This thesis proposes a method for evaluating the image quality of these new cameras. The leitmotiv of the analysis is the SNR (signal to noise ratio) of the image after deconvolution. It gives the efficiency of these new camera design in terms of image quality. The theory provides explicit formulas for the SNR. It raises two paradoxes of these cameras, and resolves them. It provides the underlying motion model of each flutter shutter, including patented ones. A shorter second part addresses the the main quality problem in infrared video imaging, the non-uniformity. This perturbation is a time-dependent noise caused by the infrared sensor, structured in columns. The conclusion of this work is that it is not only possible but also efficient and robust to perform the correction on a single image. This permits to ensure the absence of ``ghost artifacts'', a classic of the literature on the subject, coming from inadequate processing relative to the acquisition model.