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

Doctor of Philosophy

dissertationWith the ever-increasing amount of available computing resources and sensing devices, a wide variety of high-dimensional datasets are being produced in numerous fields. The complexity and increasing popularity of these data have led to new challenges and opportunities in visualization. Since most display devices are limited to communication through two-dimensional (2D) images, many visualization methods rely on 2D projections to express high-dimensional information. Such a reduction of dimension leads to an explosion in the number of 2D representations required to visualize high-dimensional spaces, each giving a glimpse of the high-dimensional information. As a result, one of the most important challenges in visualizing high-dimensional datasets is the automatic filtration and summarization of the large exploration space consisting of all 2D projections. In this dissertation, a new type of algorithm is introduced to reduce the exploration space that identifies a small set of projections that capture the intrinsic structure of high-dimensional data. In addition, a general framework for summarizing the structure of quality measures in the space of all linear 2D projections is presented. However, identifying the representative or informative projections is only part of the challenge. Due to the high-dimensional nature of these datasets, obtaining insights and arriving at conclusions based solely on 2D representations are limited and prone to error. How to interpret the inaccuracies and resolve the ambiguity in the 2D projections is the other half of the puzzle. This dissertation introduces projection distortion error measures and interactive manipulation schemes that allow the understanding of high-dimensional structures via data manipulation in 2D projections

Paraglide: Interactive Parameter Space Partitioning for Computer Simulations

In this paper we introduce paraglide, a visualization system designed for interactive exploration of parameter spaces of multi-variate simulation models. To get the right parameter configuration, model developers frequently have to go back and forth between setting parameters and qualitatively judging the outcomes of their model. During this process, they build up a grounded understanding of the parameter effects in order to pick the right setting. Current state-of-the-art tools and practices, however, fail to provide a systematic way of exploring these parameter spaces, making informed decisions about parameter settings a tedious and workload-intensive task. Paraglide endeavors to overcome this shortcoming by assisting the sampling of the parameter space and the discovery of qualitatively different model outcomes. This results in a decomposition of the model parameter space into regions of distinct behaviour. We developed paraglide in close collaboration with experts from three different domains, who all were involved in developing new models for their domain. We first analyzed current practices of six domain experts and derived a set of design requirements, then engaged in a longitudinal user-centered design process, and finally conducted three in-depth case studies underlining the usefulness of our approach

Addressing entrenched disadvantage in Australia

An estimated four to six per cent of Australia\u27s population experiences chronic or persistent poverty or deprivation. Executive Summary Entrenched disadvantage is a wicked problem for any society. Disadvantage of one form or another will always be with us, but when disadvantage is entrenched, some Australians are not able to play their full part in our economy and society. An estimated four to six per cent of our society experiences chronic or persistent poverty or deprivation. This represents both a tragedy for the individuals concerned and a loss of economic potential for the nation. While we have policies in place or in development to address disadvantage, it is not clear that we have recognised the need to address the deeper problem of long-term, persistent and chronic disadvantage. As a rich and successful society, we can clearly do better – others do. Two aspects of entrenched disadvantage are clear: The problem is both significant and complex; and Current policies to remove entrenchment are not working. The people who find it hardest to escape from disadvantage appear to fall into six main categories: 1. Older people; 2. Less-educated people; 3. Households with no employed members; 4. Particular geographic areas; 5. Indigenous Australians; and 6. Those with chronic health problems. Current policies are mainly designed to get people into, or back into, the labour market. While this is an appropriate objective, there are people in our society who need targeted and/or additional help to prepare themselves for ongoing employment. It is difficult to get or hold a job if you do not have anywhere to sleep or have ongoing health problems. It is hardly surprising then that disadvantage is cumulative: The longer a person spends with significant disadvantage, the more likely he or she is to be stuck there. Children who grow up in a home with entrenched disadvantage are also more likely to face the same problem. Related identifier: ISBN 0 85801 299

Aerospace Medicine and Biology. A continuing bibliography with indexes

This bibliography lists 244 reports, articles, and other documents introduced into the NASA scientific and technical information system in February 1981. Aerospace medicine and aerobiology topics are included. Listings for physiological factors, astronaut performance, control theory, artificial intelligence, and cybernetics are included