Recently, solutions to the problem of image segmentation and denoising are developed based on the Mumford-Shah model. The model provides an energy functional, called the Mumford-Shah functional, which should be minimized. Since the minimization of the functional has some difficulties, approximate approaches are proposed. Two such methods are the gradient flows method and the Chan-Vese active contour method. The performance evolution in terms of speed shows that the gradient flows method converges to the boundaries of the smooth parts faster / but for the hierarchical four-phase segmentation, it is observed that this method sometimes gives unsatisfactory results. In this work, a fast hierarchical four-phase segmentation method is proposed where the Chan-Vese active contour method is applied following the gradient flows method. After the segmentation process, the segmented regions are denoised using diffusion filters. Additionally, for the low signal-to-noise ratio applications, the prefiltering scheme using nonlinear diffusion filters is included in the proposed method. Simulations have shown that the proposed method provides an effective solution to the image segmentation and denoising problem.

From angry torch-swinging Parisians attacking the Bastille and Russian workers rising up against the Tsar to outraged Chinese peasants exacting revenge on their landlords and Cuban guerrillas battling Batista’s army, revolutions without violence have in the past been near inconceivable. But when unarmed Iranians after an extended popular struggle forced Muhammad Reza Pahlavi, the last king of Iran, to flee Tehran on January 16, 1979, they had gifted the world a new and seemingly paradoxical phenomenon: a nonviolent revolution. Far from a historical oddity, such revolutions have since occurred on almost every continent. Over the past thirty years the function of guerrilla tactics, military coups, and civil war has increasingly been replaced by demonstrations, boycotts, and strikes. How can social scientists account for this “evolution of revolution” that have so altered the appearance of the phenomenon that by Arendt’s definition events in places like Iran, the Philippines, Chile, Poland, East Germany, Czechoslovakia, Serbia, Georgia, and Ukraine may not even qualify as revolutions? Yet, the popular overthrows of authoritarian regimes in each and every one of those countries were nothing less than revolutionary. The dissertation seeks to understand this recent development in the nature of revolutions by historically examining the phenomenon’s signal case, the Iranian Revolution. The core question asked is: what are the structural and historical forces that caused the Iranian Revolution to be the world’s first nonviolent revolution? The central argument is that both the emergence and success of the nonviolent Iranian Revolution can be explained by its internationalization. In other words, the Iranian Revolution turned out to be successfully nonviolent because, unlike previous revolutions, it was a global affair in which the revolutionaries intentionally and strategically sought to bring the world into their struggle against the state. Indirectly, the aim of this study is to generate the genesis of a theoretical framework that can explain more broadly the emergence and success of nonviolent revolutions in the late 1970s and beyond. / text

The text covers the theory of the Mumford and Shah model for digital image segmentation. The strong and weak formulation is presented and the questions of existence, uniqueness, and solution regularity is answered. Then, a particular variant of the model called `active contours without edges' is numerically implemented. This implementation is tested on several images, the results are presented in detail and theoretically explained.

The purpose of this paper is to analyse how India’s Minister of Home Affairs, Amit Shah, constructs the image of minorities and refugees in articles, speeches, and on social media platforms. The analysis is performed with the method of qualitative content analysis within a theoretical framework of propaganda put against the backdrop of Hindu nationalism. The main analysis is divided into four categories, based upon Jowett and O'Donnell’s model of analysing propaganda, going into the themes of: context surrounding the speech; communalism; values; and target audience. This paper argues that Amit Shah’s speech in the upper house of the parliament of India, is a part of a larger Hindu nationalist campaign concerning questions of Indian identity that dates back to, at least, the early 20th century.

This thesis analyzes an anonymous portrait painting of the Ottoman Sultan Mahmud II (r. 1808-1839), called by its descriptive title Seated Portrait of Mahmud II, within the context of the extensive portrait campaign commissioned by the sultan. Surviving examples from this series of diplomatic portraits share a unique set of intercultural iconographic vocabularies as a reflection of their time as well as implicit reinforcement of the sultan's political goals. By focusing on Seated Portrait of Mahmud II, I argue that a closer inspection of the campaign within a context that pays attention to Ottoman, European, and Persian visual practices reveals a more accurate and comprehensive understanding of its cross-cultural histories and visual as well as ideological references. Structured to reflect the tripartite composition of the artwork itself, this thesis addresses the style and iconographies of the background, middleground, and foreground, respectively. Following a focused examination of the sultan's portrait, I compare Seated Portrait of Mahmud II to two contemporary paintings: Napoléon Bonaparte as First Consul (1808) from France and Portrait of Qajar Ali Shah Seated on a Chair Throne (1807) from Qajar Iran. While bringing attention to the art-historical implications of a hitherto understudied, yet significant portrait of Mahmud II, my work reexamines the early-modern history of Ottoman art within the larger framework of cross-cultural encounters.

In this thesis, the image segmentation methods based on the Mumford&amp / #8211 / Shah variational approach have been studied. By obtaining an optimum point of the Mumford-Shah functional which is a piecewise smooth approximate image and a set of edge curves, an image can be decomposed into regions. This piecewise smooth approximate image is smooth inside of regions, but it is allowed to be discontinuous region wise. Unfortunately, because of the irregularity of the Mumford Shah functional, it cannot be directly used for image segmentation. On the other hand, there are several approaches to approximate the Mumford-Shah functional. In the first approach, suggested by Ambrosio-Tortorelli, it is regularized in a special way. The regularized functional (Ambrosio-Tortorelli functional) is supposed to be gamma-convergent to the Mumford-Shah functional. In the second approach, the Mumford-Shah functional is minimized in two steps. In the first minimization step, the edge set is held constant and the resultant functional is minimized. The second minimization step is about updating the edge set by using level set methods. The second approximation to the Mumford-Shah functional is known as the Chan-Vese method. In both approaches, resultant PDE equations (Euler-Lagrange equations of associated functionals) are solved by finite difference methods. In this study, both approaches are implemented in a MATLAB environment. The overall performance of the algorithms has been investigated based on computer simulations over a series of images from simple to complicated.

Late in 2004, King Abdullah of Jordan coined a controversial phrase that still dominates the heart of the geopolitics of the Middle East: The Shia Crescent. “If pro-Iran parties or politicians dominate the new Iraqi government, a new ‘crescent’ of dominant Shia movements or governments stretching from Iran into Iraq, Syria, and Lebanon could emerge to alter the traditional balance of power between the two main Islamic sects and pose new challenges to U.S. interests and allies. What the King of Jordan saw as a threat, Iran saw as the bedrock of its newfound regional power. However, what the King of Jordan and his Arab-Sunni aides downplayed was Iran’s ties with non-Shia groups, ranging from Sunni parties to secular and even non-Muslim groups. More importantly, they neglected Iran’s presence in the Middle East before the 1979 Islamic Revolution. In fact, the seeming omnipresence of Iran’s proxies in the Middle East is not a recent, nuanced phenomenon; rather, it dated back to the Shah’s foreign policy in making connections with both the Iraqi Kurds and Shia Lebanese. While much ink has been spilled on Iran’s foreign policy under the Islamic Republic, there has been a void in the analysis of Iran’s ties with Non-State Actors (NSAs) in the pre-1979 Revolution Era. v From this point of view, the present study is an attempt to set forth a new understanding of the emergence and fluctuation of Iran’s ties with NSAs at the heart of the Middle East during the Shah’s era. I will accomplish this by identifying the Iran-NSA relationships within an examination of the larger historical context of state-NSA relationships in the region. Here, the story of the evolution of Iran’s ties with NSAs can be narrated as the unfolding of constant interaction between states and non-state forces in the Middle East. Analyzed from this perspective, my research examines the actors, processes, and mechanisms that Iran has used to construct ties with NSAs from 1961 until 1979. “What actors and processes at what levels of analysis and through what mechanisms have constructed Iran’s ties with NSAs?” This is the central question that guides the analytical narrative in the present survey. Therefore, the dependent variable for this research is the evolution of Iran’s ties with NSAs, while the intervening variable is a set of actors and processes that have brought about such sub-state ties. In this framework, the proposed work will undertake these main tasks: A) Tracing the history of the ebbs and flows within Iran’s ties with non-state actors through a geopolitical lens. B) Explaining how Iran’s ties with non-state actors unfolded and understanding why Iran’s proxies evolved in the way they did. C) AssessingthebroadcontoursoftheevolutionarytrajectoryofIran’stieswithNSAs and its possible future path(s) for the geopolitics of the Middle East and its regional balance of power.

Most applications in computer vision suffer from two major difficulties. The first is they are notoriously ridden with sub-optimal local minima. The second is that they typically require high computational cost to be solved robustly. The reason for these two drawbacks is that most problems in computer vision, even when well-defined, typically require finding a solution in a very large high-dimensional space. It is for these two reasons that multiscale methods are particularly well-suited to problems in computer vision. Multiscale methods, by way of looking at the coarse scale nature of a problem before considering the fine scale nature, often have the ability to avoid sub-optimal local minima and obtain a more globally optimal solution. In addition, multiscale methods typically enjoy reduced computational cost. This thesis applies novel multiscale active contour methods to several problems in computer vision, especially in simultaneous segmentation and reconstruction of tomography images. In addition, novel multiscale methods are applied to contour registration using minimal surfaces and to the computation of non-linear rotationally invariant optical flow. Finally, a methodology for fast robust image segmentation is presented that relies on a lower dimensional image basis derived from an image scale space. The specific advantages of using multiscale methods in each of these problems is highlighted in the various simulations throughout the thesis, particularly their ability to avoid sub-optimal local minima and their ability to solve the problems at a lower overall computational cost.

Abdullah Shah (1680-1757) was the birth name of the boy who would later become one of the most eminent Sufi poets of South Asia, and the master of Sufi lyrics in Punjabi—Bulleh Shah. Living during times of strife and major conflict between the Sikhs and the crumbling Mughal Empire, Bulleh Shah wrote poetry with an underlying humanist and tolerant philosophy that challenged the turmoil of his times. Blind to the bounds of religion and caste in an increasingly divided India, Bullah’s spiritual philosophy and his message of equality found voice in his kafis—a genre of poetry indigenous to the Indian subcontinent that can be seen as a form of folk ballad. This project offers translations of 15 kafis from his identifiable corpus, preceded by a substantial introductionFurthermore, the project is accompanied. Each kafi is presented in three translations—literal, functional, and oral. The selected kafis draw on the three dominant themes in his work—Ishq, rebellion, and freedom. Scans of the original kafis in Shahmuki script Punjabi have been provided. Furthermore, the project is accompanied by an interpretive composition of the translated kafi “What Times, What Strange Times,” which was a collaboration between the author of the thesis, Akshaya Tucker, and Jacob Scharfman.

Dans cette thèse, nous nous proposons d'étudier et de traiter conjointement plusieurs problèmes phares en traitement d'images incluant le recalage d'images qui vise à apparier deux images via une transformation, la segmentation d'images dont le but est de délimiter les contours des objets présents au sein d'une image, et la décomposition d'images intimement liée au débruitage, partitionnant une image en une version plus régulière de celle-ci et sa partie complémentaire oscillante appelée texture, par des approches variationnelles locales et non locales. Les relations étroites existant entre ces différents problèmes motivent l'introduction de modèles conjoints dans lesquels chaque tâche aide les autres, surmontant ainsi certaines difficultés inhérentes au problème isolé. Le premier modèle proposé aborde la problématique de recalage d'images guidé par des résultats intermédiaires de segmentation préservant la topologie, dans un cadre variationnel. Un second modèle de segmentation et de recalage conjoint est introduit, étudié théoriquement et numériquement puis mis à l'épreuve à travers plusieurs simulations numériques. Le dernier modèle présenté tente de répondre à un besoin précis du CEREMA (Centre d'Études et d'Expertise sur les Risques, l'Environnement, la Mobilité et l'Aménagement) à savoir la détection automatique de fissures sur des images d'enrobés bitumineux. De part la complexité des images à traiter, une méthode conjointe de décomposition et de segmentation de structures fines est mise en place, puis justifiée théoriquement et numériquement, et enfin validée sur les images fournies. / In this thesis, we study and jointly address several important image processing problems including registration that aims at aligning images through a deformation, image segmentation whose goal consists in finding the edges delineating the objects inside an image, and image decomposition closely related to image denoising, and attempting to partition an image into a smoother version of it named cartoon and its complementary oscillatory part called texture, with both local and nonlocal variational approaches. The first proposed model addresses the topology-preserving segmentation-guided registration problem in a variational framework. A second joint segmentation and registration model is introduced, theoretically and numerically studied, then tested on various numerical simulations. The last model presented in this work tries to answer a more specific need expressed by the CEREMA (Centre of analysis and expertise on risks, environment, mobility and planning), namely automatic crack recovery detection on bituminous surface images. Due to the image complexity, a joint fine structure decomposition and segmentation model is proposed to deal with this problem. It is then theoretically and numerically justified and validated on the provided images.