With advances in imaging and communication systems, there is increased use of multi-dimensional images. Examples include multi-view image/video, hyperspectral image/video and dynamic volume imaging in CT/MRI/Ultrasound. These datasets consume even larger amounts of resources for transmission or storage compared to 2-D images. Hence, it is vital to have efficient compression methods for multi-dimensional images. In this dissertation, first, a JPEG2000 Part-2 compliant scheme is proposed for compressing multi-dimensional datasets for any dimension N>=3. Secondly, a novel view-compensated compression method is investigated for remote visualization of volumetric data. Experimental results indicate superior compression performance compared to state-of-the-art compression standards. Thirdly, a new scalable low complexity coder is designed that sacrifices some compression efficiency to get substantial gain in throughput. Potential use of the scalable low complexity coder is illustrated for two applications: Airborne video transmission and remote volume visualization.

This research aimed to investigate the use of geo-spatial information product in decision-making within area under local government. The choice of methods is of crucial importance in the understanding and adoption by the potential users. The efficiency of symbols and readability of information is paramount in conveying information. Observation of the local population's use of language and symbology was incorporated into this work in order to show possible representations that would be more meaningful to the reader.The base of the geo-spatial product developed in this was developed our research on the impact of urbanization on ground water resources. The research examined the urbanization impact on ground water quality and level translated through nitrate level and ground water level. The use of maps as decision-making tools with different symbol representation of nitrate and water level presents a potentially simple method for decision makers who are not necessarily experts, but are the ones making the final political decision. The collection and processing of multi-source data requires the reorganization of the data in a meaningful way.

Project Management is the primary key to successful software development. In 1995 Caper Jones stated that the failure or cancellation rate of large software systems was over 20% in his article on patterns of large software systems. More than two thirds of the projects fail due to improper management of skills, activities, and personnel. One main reason is that software is not a tangible entity and is hard to visualize and hence to monitor. A manager has to be skilled in different CASE tools and technologies to track and manage a software development process successfully. The volume of results produced by these CASE tools is so huge that a high level manager cannot look into all the details. He has to get a high level picture of the project, to know where the project is heading, and if needed, then look into the finer level details by drilling down to locate and correct problems. The objective of this thesis is to build an Advanced Charting System (ACS), which would act as a companion to PAMPA 2 (Project Attribute Monitoring and Prediction Associate) and help a manager visualize the state of a software project over a standard World Wide Web browser. The PAMPA 2 ACS will be responsible for visualizing and tracking of resources, tasks, schedules and milestones of a software project described in the plan. PAMPA 2 ACS will have the ability to depict the status of the project through a variety of graphs and charts. PAMPA 2 ACS implements a novel charting technique called as DOT Chart to track the processes and activities of a software project. PAMPA 2 ACS provides a multilevel view of the project status. PAMPA 2 ACS will be able to track any arbitrary plan starting from a collapsed / concise view of a whole project. This can be further drilled down to the lowest level of detail. The status can be viewed at the project version level, plan and workbreakdown levels, process, sub process, and activity level. Among all the process models, the DOT charts can be applied effectively to spiral process model where each spiral represents a project version.

We present Glimmer, a new multilevel visualization algorithm for multidimensional scaling designed to exploit modern graphics processing unit (GPU) hard-ware. We also present GPU-SF, a parallel, force-based subsystem used by Glimmer. Glimmer organizes input into a hierarchy of levels and recursively applies GPU-SF to combine and refine the levels. The multilevel nature of the algorithm helps avoid local minima while the GPU parallelism improves speed of computation. We propose a robust termination condition for GPU-SF based on a filtered approximation of the normalized stress function. We demonstrate the benefits of Glimmer in terms of speed, normalized stress, and visual quality against several previous algorithms for a range of synthetic and real benchmark datasets. We show that the performance of Glimmer on GPUs is substantially faster than a CPU implementation of the same algorithm. We also propose a novel texture paging strategy called distance paging for working with precomputed distance matrices too large to fit in texture memory.

In decision theory the process of selecting the best option is called preferential choice. Many personal, business, and professional preferential choice decisions are made every day. In these situations, a decision maker must select the optimal option among multiple alternatives. In order to do this, she must be able to analyze a model of her preferences with respect to the objectives that are important to her. Prescriptive decision theory suggests several ways to effectively develop a decision model. However, these methods often end up too tedious and complicated to apply to complex decisions that involve many objectives and alternatives. In order to help people make better decisions, an easier, more intuitive way to develop interactive models for analysis of decision contexts is needed. The application of interactive visualization techniques to this problem is an opportune solution. A visualization tool to help in preferential choice must take into account important aspects from both fields of Information Visualization and Decision Theory. There exists some proposals that claim to aid preferential choice, but some key tasks and steps from at least one of these areas are often overlooked. An added missing element in these proposals is an adequate user evaluation. In fact, the concept of a good evaluation in the field of information visualization is a topic of debate, since the goals of such systems stretch beyond what can be concluded from traditional usability testing. In our research we investigate ways to overcome some of the challenges faced in the design and evaluation of visualization systems for preferential choice. In previous work, Carenini and Lloyd proposed ValueCharts, a set of visualizations and interactive techniques to support the inspection of linear models of preferences. We now identify the need to consider the decision process in its entirety, and to redesign ValueCharts in order to support all phases of preferential choice. We present our task-based approach to the redesign of ValueCharts grounded in recent findings from both Decision Analysis and Information Visualization. We propose a set of domain-independent tasks for the design and evaluation of interactive visualizations for preferential choice. We then use the resulting framework as a basis for an analytical evaluation of our tool and alternative approaches. Finally, we use an application of the task model in conjunction with a new blend of evaluation methods to assess the utility of ValueCharts.

Organizing personal collections of digital documents can be frustrating for two main reasons. First, the effort required to work with the folder system on personal computers and the possible misplacement and loss of documents. Second, the lack of effective organization and management tools for personal collections of digital documents. The research in this thesis investigated specific visualization and clustering features intended for organizing collections of documents and built in a prototype interface that was compared to a baseline interface from previous research. The results showed that those features helped users with: 1) the initial classification of documents into clusters during the supervised stage; 2) the modification of clusters; 3) the cluster labeling process; 4) the presentation of the final set of organized documents; 5) the efficiency of the organization process, and 6) achieving better accuracy in the clusters created for organizing the documents.

This study integrated and applied effective communication concepts to highlight landscape as both medium and method to improve land use decisions, in the face of uncertainty, such as that posed by global climate change. Grounded theory guided the emergence of a communication model to illustrate impacts of land use scenarios in a study area. Scenarios incorporated socioeconomic trends and biophysical data, including localized climate projections and relevant audience traits assumed from prior assessments. Scenario implications were analyzed by comparing their ecological service values; the communication model’s effectiveness was evaluated against principles derived from the literature. Results suggest that a communication framework grounded in landscape can improve comprehension of environmental and human needs; however, further testing is needed. This framework can help enable broader landscape understanding through shared experience and engagement. Enhancing communication channels in this way is required as increasingly complex environmental problems demand more collaborative and communal solutions. / Landscape Architecture Canada Foundation

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The Hubble Space Telescope has provided the world with incredible imagery of the surrounding universe. The aesthetic quality of this imagery is limited by production resources; by creating a method to harness the highly refined detail and quality of CG elements in live-action films, we can inspire and educate at a much greater level. In this thesis, I create a rendering approach that allows camera movement around and through elements such as nebulae and galaxies, creating a more cinematic experience. The solution will also allow for reasonable scientific accuracy, visual appeal, efficiency, and extendability to other astronomical visualizations. 3D meshes are constructed and textured using telescopic images as reference. Splats are volumetrically generated using a voxelized bounding box around the mesh. Valid splats within a user specified maximum distance receive initial color and alpha values from the texture map. Probability density functions are used to create a density falloff along the edges of the object, and modifications to the RGBA values are made to achieve the desired cloud-like appearance. The data sets are rendered using a C program developed at the Space Telescope Science Institute by Dr. Frank Summers. The methodology is applied to the test cases of a nebula, star-forming region Sharpless 2-106, and a galaxy, Messier 51, or the Whirlpool Galaxy. The results of this thesis demonstrate the visual, scientific, and technical success of this solution. The code developed during this project generates the desired imagery with reasonable efficiency. A short animation moving from outside the galaxy to a close up of the nebula exhibits the flexibility in scale and camera movement. A careful balance between scientific accuracy and visual appeal were maintained through consultation with astronomers at the Space Telescope Science Institute. The favorable efficient, flexible, visual, and scientific results presented by this work make this process extendable to most other cases of nebula and galaxy visualizations.