Recent Progress in Image Deblurring

This paper comprehensively reviews the recent development of image deblurring, including non-blind/blind, spatially invariant/variant deblurring techniques. Indeed, these techniques share the same objective of inferring a latent sharp image from one or several corresponding blurry images, while the blind deblurring techniques are also required to derive an accurate blur kernel. Considering the critical role of image restoration in modern imaging systems to provide high-quality images under complex environments such as motion, undesirable lighting conditions, and imperfect system components, image deblurring has attracted growing attention in recent years. From the viewpoint of how to handle the ill-posedness which is a crucial issue in deblurring tasks, existing methods can be grouped into five categories: Bayesian inference framework, variational methods, sparse representation-based methods, homography-based modeling, and region-based methods. In spite of achieving a certain level of development, image deblurring, especially the blind case, is limited in its success by complex application conditions which make the blur kernel hard to obtain and be spatially variant. We provide a holistic understanding and deep insight into image deblurring in this review. An analysis of the empirical evidence for representative methods, practical issues, as well as a discussion of promising future directions are also presented.Comment: 53 pages, 17 figure

Diagnostics Examples from Third-Generation Light Sources

This lesson discusses many examples of how the signals from the beam monitors are used to diagnose the beam in circular, third-generation synchrotron light sources. During the school, diagnostic examples in other machines (e.g. colliders, CTF3, linacs and free-electron lasers (FEL), and medical accelerators) were given in other lectures. This lesson assumes that the signal generation in the instrument itself is already known; the main focus lies on the dependence of the signals on various machine parameters and their interpretation to diagnose the machine parameters and conditions.Comment: 22 pages, contribution to the CAS - CERN Accelerator School: Beam Instrumentation, 2-15 June 2018, Tuusula, Finlan

Camera System Performance Derived from Natural Scenes

The Modulation Transfer Function (MTF) is a well-established measure of camera system performance, commonly employed to characterize optical and image capture systems. It is a measure based on Linear System Theory; thus, its use relies on the assumption that the system is linear and stationary. This is not the case with modern-day camera systems that incorporate non-linear image signal processes (ISP) to improve the output image. Non-linearities result in variations in camera system performance, which are dependent upon the specific input signals. This paper discusses the development of a novel framework, designed to acquire MTFs directly from images of natural complex scenes, thus making the use of traditional test charts with set patterns redundant. The framework is based on extraction, characterization and classification of edges found within images of natural scenes. Scene derived performance measures aim to characterize non-linear image processes incorporated in modern cameras more faithfully. Further, they can produce ‘live’ performance measures, acquired directly from camera feeds

Somaesthetics and Dance

Dance is proposed as the most representative of somaesthetic arts in Thinking Through the Body: Essays in Somaesthetics and other writings of Richard Shusterman. Shuster- man offers a useful, but incomplete approach to somaesthetics of dance. In the examples provided, dance appears as subordinate to another art form (theater or photography) or as a means to achieving bodily excellence. Missing, for example, are accounts of the role of dance as an independent art form, how somaesthetics would address differences in varying approaches to dance, and attention to the viewer’s somaesthetic dance experience. Three strategies for developing new directions for dance somaesthetics are offered here: identify a fuller range of applications of somaesthetics to dance as an independent art form (e.g. Martha Graham); develop somaesthetics for a wider range of theatre dance (e.g. ballet, modern and experimental dance); and relate somaesthetics to more general features of dance (content, form, expression, style, kinesthetics) necessary for understanding the roles of the choreographer/dancer and the viewer

Supervised learning of an opto-magnetic neural network with ultrashort laser pulses

The explosive growth of data and its related energy consumption is pushing the need to develop energy-efficient brain-inspired schemes and materials for data processing and storage. Here, we demonstrate experimentally that Co/Pt films can be used as artificial synapses by manipulating their magnetization state using circularly-polarized ultrashort optical pulses at room temperature. We also show an efficient implementation of supervised perceptron learning on an opto-magnetic neural network, built from such magnetic synapses. Importantly, we demonstrate that the optimization of synaptic weights can be achieved using a global feedback mechanism, such that the learning does not rely on external storage or additional optimization schemes. These results suggest there is high potential for realizing artificial neural networks using optically-controlled magnetization in technologically relevant materials, that can learn not only fast but also energy-efficient.Comment: 9 pages, 4 figure

Coordination of Dynamic Software Components with JavaBIP

JavaBIP allows the coordination of software components by clearly separating the functional and coordination aspects of the system behavior. JavaBIP implements the principles of the BIP component framework rooted in rigorous operational semantics. Recent work both on BIP and JavaBIP allows the coordination of static components defined prior to system deployment, i.e., the architecture of the coordinated system is fixed in terms of its component instances. Nevertheless, modern systems, often make use of components that can register and deregister dynamically during system execution. In this paper, we present an extension of JavaBIP that can handle this type of dynamicity. We use first-order interaction logic to define synchronization constraints based on component types. Additionally, we use directed graphs with edge coloring to model dependencies among components that determine the validity of an online system. We present the software architecture of our implementation, provide and discuss performance evaluation results.Comment: Technical report that accompanies the paper accepted at the 14th International Conference on Formal Aspects of Component Softwar