Evaluation of the color image and video processing chain and visual quality management for consumer systems

With the advent of novel digital display technologies, color processing is increasingly becoming a key aspect in consumer video applications. Today’s state-of-the-art displays require sophisticated color and image reproduction techniques in order to achieve larger screen size, higher luminance and higher resolution than ever before. However, from color science perspective, there are clearly opportunities for improvement in the color reproduction capabilities of various emerging and conventional display technologies. This research seeks to identify potential areas for improvement in color processing in a video processing chain. As part of this research, various processes involved in a typical video processing chain in consumer video applications were reviewed. Several published color and contrast enhancement algorithms were evaluated, and a novel algorithm was developed to enhance color and contrast in images and videos in an effective and coordinated manner. Further, a psychophysical technique was developed and implemented for performing visual evaluation of color image and consumer video quality. Based on the performance analysis and visual experiments involving various algorithms, guidelines were proposed for the development of an effective color and contrast enhancement method for images and video applications. It is hoped that the knowledge gained from this research will help build a better understanding of color processing and color quality management methods in consumer video

A method for generating realistic correlation matrices

Simulating sample correlation matrices is important in many areas of statistics. Approaches such as generating Gaussian data and finding their sample correlation matrix or generating random uniform $[-1,1]$ deviates as pairwise correlations both have drawbacks. We develop an algorithm for adding noise, in a highly controlled manner, to general correlation matrices. In many instances, our method yields results which are superior to those obtained by simply simulating Gaussian data. Moreover, we demonstrate how our general algorithm can be tailored to a number of different correlation models. Using our results with a few different applications, we show that simulating correlation matrices can help assess statistical methodology.Comment: Published in at http://dx.doi.org/10.1214/13-AOAS638 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Customized finite element modelling of the human cornea

Aim To construct patient-specific solid models of human cornea from ocular topographer data, to increase the accuracy of the biomechanical and optical estimate of the changes in refractive power and stress caused by photorefractive keratectomy (PRK). Method Corneal elevation maps of five human eyes were taken with a rotating Scheimpflug camera combined with a Placido disk before and after refractive surgery. Patient-specific solid models were created and discretized in finite elements to estimate the corneal strain and stress fields in preoperative and postoperative configurations and derive the refractive parameters of the cornea. Results Patient-specific geometrical models of the cornea allow for the creation of personalized refractive maps at different levels of IOP. Thinned postoperative corneas show a higher stress gradient across the thickness and higher sensitivity of all geometrical and refractive parameters to the fluctuation of the IOP. Conclusion Patient-specific numerical models of the cornea can provide accurate quantitative information on the refractive properties of the cornea under different levels of IOP and describe the change of the stress state of the cornea due to refractive surgery (PRK). Patient-specific models can be used as indicators of feasibility before performing the surgery. Copyright: © 2015 Simonini, Pandolfi

Hybrid video quality prediction: reviewing video quality measurement for widening application scope

A tremendous number of objective video quality measurement algorithms have been developed during the last two decades. Most of them either measure a very limited aspect of the perceived video quality or they measure broad ranges of quality with limited prediction accuracy. This paper lists several perceptual artifacts that may be computationally measured in an isolated algorithm and some of the modeling approaches that have been proposed to predict the resulting quality from those algorithms. These algorithms usually have a very limited application scope but have been verified carefully. The paper continues with a review of some standardized and well-known video quality measurement algorithms that are meant for a wide range of applications, thus have a larger scope. Their individual artifacts prediction accuracy is usually lower but some of them were validated to perform sufficiently well for standardization. Several difficulties and shortcomings in developing a general purpose model with high prediction performance are identified such as a common objective quality scale or the behavior of individual indicators when confronted with stimuli that are out of their prediction scope. The paper concludes with a systematic framework approach to tackle the development of a hybrid video quality measurement in a joint research collaboration.Polish National Centre for Research and Development (NCRD) SP/I/1/77065/10, Swedish Governmental Agency for Innovation Systems (Vinnova

Structural engineering of evolving complex dynamical networks

Networks are ubiquitous in nature and many natural and man-made systems can be modelled as networked systems. Complex networks, systems comprising a number of nodes that are connected through edges, have been frequently used to model large-scale systems from various disciplines such as biology, ecology, and engineering. Dynamical systems interacting through a network may exhibit collective behaviours such as synchronisation, consensus, opinion formation, flocking and unusual phase transitions. Evolution of such collective behaviours is highly dependent on the structure of the interaction network. Optimisation of network topology to improve collective behaviours and network robustness can be achieved by intelligently modifying the network structure. Here, it is referred to as "Engineering of the Network". Although coupled dynamical systems can develop spontaneous synchronous patterns if their coupling strength lies in an appropriate range, in some applications one needs to control a fraction of nodes, known as driver nodes, in order to facilitate the synchrony. This thesis addresses the problem of identifying the set of best drivers, leading to the best pinning control performance. The eigen-ratio of the augmented Laplacian matrix, that is the largest eigenvalue divided by the second smallest one, is chosen as the controllability metric. The approach introduced in this thesis is to obtain the set of optimal drivers based on sensitivity analysis of the eigen-ratio, which requires only a single computation of the eigenvector associated with the largest eigenvalue, and thus is applicable for large-scale networks. This leads to a new "controllability centrality" metric for each subset of nodes. Simulation results reveal the effectiveness of the proposed metric in predicting the most important driver(s) correctly.     Interactions in complex networks might also facilitate the propagation of undesired effects, such as node/edge failure, which may crucially affect the performance of collective behaviours. In order to study the effect of node failure on network synchronisation, an analytical metric is proposed that measures the effect of a node removal on any desired eigenvalue of the Laplacian matrix. Using this metric, which is based on the local multiplicity of each eigenvalue at each node, one can approximate the impact of any node removal on the spectrum of a graph. The metric is computationally efficient as it only needs a single eigen-decomposition of the Laplacian matrix. It also provides a reliable approximation for the "Laplacian energy" of a network. Simulation results verify the accuracy of this metric in networks with different topologies. This thesis also considers formation control as an application of network synchronisation and studies the "rigidity maintenance" problem, which is one of the major challenges in this field. This problem is to preserve the rigidity of the sensing graph in a formation during motion, taking into consideration constraints such as line-of-sight requirements, sensing ranges and power limitations. By introducing a "Lattice of Configurations" for each node, a distributed rigidity maintenance algorithm is proposed to preserve the rigidity of the sensing network when failure in a sensing link would result in loss of rigidity. The proposed algorithm recovers rigidity by activating, almost always, the minimum number of new sensing links and considers real-time constraints of practical formations. A sufficient condition for this problem is proved and tested via numerical simulations. Based on the above results, a number of other areas and applications of network dynamics are studied and expounded upon in this thesis

Pressure Field Measurements in a Helical Coil Steam Generator Model Using Pressure Sensitive Paint

Helical coil heat exchangers are types of tube and shell heat exchangers that have been implemented in processing plants, oil and gas, and refrigeration. Currently several designs have been proposed for next generation nuclear power plant designs, such as small modular reactors, high temperature reactors, and molten salt reactors. Helical coil designs are under consideration due to their compact designs and superior heat transfer efficiencies when compared to straight pipe designs. Designs are characterized by the geometry of the tube bundle, which is described as either in-line (square) or staggered (triangular). This study focuses on a helical coil design that has interlacing tube bundles, which causes the tube bundle geometry to shift between in-line and staggered. Cross sectional geometries have been previously correlated to pressure drop, friction factor, and heat transfer efficiencies depending on parameters such as pitch, tube sizing, and spacing between tubes. Additionally, tube bundles with staggered arrangements are known to cause additional disruptions in the flow which can lead to more turbulence between the tubes. Studying the effects of the tube bundle arrangement on shell side flow has typically been done by measuring pressure drops and temperature changes using pressure transducers and thermocouples respectively. This study uses the pressure sensitive paint technique to analyze pressure distributions on the surface of the tubes, and validates measurements by comparing them to static pressure transducers. Pressure sensitive paint is a technique commonly used in aerospace research studies. This technique utilizes a luminescent dye that reacts to the partial pressure of oxygen, allowing full field pressure measurements on an objects surface. Experiments using pressure sensitive paint were performed on a helical coil steam generator model at Re 4000, 6000, 8500, and 11600. Two different paint formulations were used to develop instantaneous and average pressure distributions on the surface of the tubes. This study outlines the development of a wind tunnel containing a helical coil steam generator model, and presents full field pressure measurements on the surface of tubes. Measurements show that the interlacing tube bundle geometry causes significant turbulence on tubes in the developed region of flow, but the pressure distributions are dependent upon tube location. This means adjacent tubes in the same bundle were found to not share similar pressure distribution patterns