Enhanced perception in volume visualization

Due to the nature of scientic data sets, the generation of convenient visualizations may be a difficult task, but crucial to correctly convey the relevant information of the data. When working with complex volume models, such as the anatomical ones, it is important to provide accurate representations, since a misinterpretation can lead to serious mistakes while diagnosing a disease or planning surgery. In these cases, enhancing the perception of the features of interest usually helps to properly understand the data. Throughout years, researchers have focused on different methods to improve the visualization of volume data sets. For instance, the definition of good transfer functions is a key issue in Volume Visualization, since transfer functions determine how materials are classified. Other approaches are based on simulating realistic illumination models to enhance the spatial perception, or using illustrative effects to provide the level of abstraction needed to correctly interpret the data. This thesis contributes with new approaches to enhance the visual and spatial perception in Volume Visualization. Thanks to the new computing capabilities of modern graphics hardware, the proposed algorithms are capable of modifying the illumination model and simulating illustrative motifs in real time. In order to enhance local details, which are useful to better perceive the shape and the surfaces of the volume, our first contribution is an algorithm that employs a common sharpening operator to modify the lighting applied. As a result, the overall contrast of the visualization is enhanced by brightening the salient features and darkening the deeper regions of the volume model. The enhancement of depth perception in Direct Volume Rendering is also covered in the thesis. To do this, we propose two algorithms to simulate ambient occlusion: a screen-space technique based on using depth information to estimate the amount of light occluded, and a view-independent method that uses the density values of the data set to estimate the occlusion. Additionally, depth perception is also enhanced by adding halos around the structures of interest. Maximum Intensity Projection images provide a good understanding of the high intensity features of the data, but lack any contextual information. In order to enhance the depth perception in such a case, we present a novel technique based on changing how intensity is accumulated. Furthermore, the perception of the spatial arrangement of the displayed structures is also enhanced by adding certain colour cues. The last contribution is a new manipulation tool designed for adding contextual information when cutting the volume. Based on traditional illustrative effects, this method allows the user to directly extrude structures from the cross-section of the cut. As a result, the clipped structures are displayed at different heights, preserving the information needed to correctly perceive them.Debido a la naturaleza de los datos científicos, visualizarlos correctamente puede ser una tarea complicada, pero crucial para interpretarlos de forma adecuada. Cuando se trabaja con modelos de volumen complejos, como es el caso de los modelos anatómicos, es importante generar imágenes precisas, ya que una mala interpretación de las mismas puede producir errores graves en el diagnóstico de enfermedades o en la planificación de operaciones quirúrgicas. En estos casos, mejorar la percepción de las zonas de interés, facilita la comprensión de la información inherente a los datos. Durante décadas, los investigadores se han centrado en el desarrollo de técnicas para mejorar la visualización de datos volumétricos. Por ejemplo, los métodos que permiten definir buenas funciones de transferencia son clave, ya que éstas determinan cómo se clasifican los materiales. Otros ejemplos son las técnicas que simulan modelos de iluminación realista, que permiten percibir mejor la distribución espacial de los elementos del volumen, o bien los que imitan efectos ilustrativos, que proporcionan el nivel de abstracción necesario para interpretar correctamente los datos. El trabajo presentado en esta tesis se centra en mejorar la percepción de los elementos del volumen, ya sea modificando el modelo de iluminación aplicado en la visualización, o simulando efectos ilustrativos. Aprovechando la capacidad de cálculo de los nuevos procesadores gráficos, se describen un conjunto de algoritmos que permiten obtener los resultados en tiempo real. Para mejorar la percepción de detalles locales, proponemos modificar el modelo de iluminación utilizando una conocida herramienta de procesado de imágenes (unsharp masking). Iluminando aquellos detalles que sobresalen de las superficies y oscureciendo las zonas profundas, se mejora el contraste local de la imagen, con lo que se consigue realzar los detalles de superficie. También se presentan diferentes técnicas para mejorar la percepción de la profundidad en Direct Volume Rendering. Concretamente, se propone modificar la iluminación teniendo en cuenta la oclusión ambiente de dos maneras diferentes: la primera utiliza los valores de profundidad en espacio imagen para calcular el factor de oclusión del entorno de cada pixel, mientras que la segunda utiliza los valores de densidad del volumen para aproximar dicha oclusión en cada vóxel. Además de estas dos técnicas, también se propone mejorar la percepción espacial y de la profundidad de ciertas estructuras mediante la generación de halos. La técnica conocida como Maximum Intensity Projection (MIP) permite visualizar los elementos de mayor intensidad del volumen, pero no aporta ningún tipo de información contextual. Para mejorar la percepción de la profundidad, proponemos una nueva técnica basada en cambiar la forma en la que se acumula la intensidad en MIP. También se describe un esquema de color para mejorar la percepción espacial de los elementos visualizados. La última contribución de la tesis es una herramienta de manipulación directa de los datos, que permite preservar la información contextual cuando se realizan cortes en el modelo de volumen. Basada en técnicas ilustrativas tradicionales, esta técnica permite al usuario estirar las estructuras visibles en las secciones de los cortes. Como resultado, las estructuras de interés se visualizan a diferentes alturas sobre la sección, lo que permite al observador percibirlas correctamente

Vicinity Occlusion Maps: Enhanced Depth Perception of Volumetric Models

Volume models often show high depth complexity. This poses di±culties to the observer in judging the spatial relationships accurately. Illustrators usually use certain techniques such as halos or edge darkening in order to enhance depth perception of certain structures. Halos may be dark or light, and even colored. Halo construction on a volumetric basis impacts rendering performance due to the complexity of the construction process. In this paper we present Vicinity Occlusion Maps: a simple and fast method to compute the light occlusion due to neighboring voxels. Vicinity Occlusion Maps may be used to generate flexible halos around objects or selected structures in order to enhance depth perception or accentuate the presence of some structures in volumetric models at a low cost. The user may freely select the structure that requires the halos to be generated, its color and size, and our proposed application generates those in real time. They may also be used to perform vicinity shading in realtime, or even to combine both effects.Peer ReviewedPostprint (author’s final draft

Feature-based Visualization of Dense Integral Line Data

Feature-based visualization of flow fields has proven as an effective tool for flow analysis. While most flow visualization techniques operate on vector field data, our visualization techniques make use of a different simulation output: Particle Tracers. Our approach solely relies on integral lines that can be easily obtained from most simulation software. The task is the visualization of dense integral line data. We combine existing methods for streamline visualization, i.e. illumination, transparency, and halos, and add ambient occlusion for lines. But, this only solves one part of the problem: because of the high density of lines, visualization has to fight with occlusion, high frequency noise, and overlaps. As a solution we propose non-automated choices of transfer functions on curve properties that help highlighting important flow features like vortices or turbulent areas. These curve properties resemble some of the original flow properties. With the new combination of existing line drawing methods and the addition of ambient occlusion we improve the visualization of lines by adding better shape and depth cues. The intelligent use of transfer functions on curve properties reduces visual clutter and helps focusing on important features while still retaining context, as demonstrated in the examples given in this work

Combined surface and volumetric occlusion shading

Journal ArticleIn this paper, a method for interactive direct volume rendering is proposed that computes ambient occlusion effects for visualizations that combine both volumetric and geometric primitives, specifically tube shaped geometric objects representing streamlines, magnetic field lines or DTI fiber tracts. The proposed algorithm extends the recently proposed Directional Occlusion Shading model to allow the rendering of those geometric shapes in combination with a context providing 3D volume, considering mutual occlusion between structures represented by a volume or geometry