Philip K. Robertson

Visualizing color gamuts: a user interface for the effective use of perceptual color spaces in data displays

The advantages of using perceptually uniform color spaces in data displays are described. It is shown how one-, two-, and three-dimensional representations of color gamuts can provide an understanding, at various visualization levels, of the colors that can be produced on display devices, of how they restrict color displays in practice, and of how they form an essential part of a user interface in the design of color displays.<<ETX>>

The Generation of Color Sequences for Univariate and Bivariate Mapping

Recent technological advances have made it feasible to produce full color statistical maps on computer-controlled display systems. This has caused an appraisal of the use of color to represent statistical variables, and the development of a theoretical structure for the choice of suitable univariate and bivariate map coloring schemes. Realization of such schemes in an intuitive and controlled way is important to the comprehension of statistical variables from maps. Therefore, we present a method of generating specific color sequences within the framework of a uniform color space, allowing for the intuitive specification of color sequences and for their realization on various display systems.

Volume rendering on the MasPar MP-1

This work presents the implementation of data-parallel perspective volume rendering on a massively parallel SIMD computer, the MasPar MP-1, and shows the benefits of e

A methodology for choosing data representations

icient indirect addressing (an MP-1 feature) which allows individual processing elements to address their local memory independently. Emphasis is put on the geometric transformations required for volume rendering algorithms. TJte data-parallel algorithm separates multi-dimensional spatial transformations into a series of one-dimensional operations that can be performed in parallel on regular data domains, providing performance linear with data size. The rotation andperspective transformation is reduced to four shearlscale passes. The separable approach allows for predictable and regular data handling, independent of data values, allowing optimization of communication between processing elements. The communications required are data axis transpositions, wJtich can be peflormed using the MP-1 ‘s global router, which delivers scalable peflormance. Wrtualization allows graceful scaling in both problem size and architecture size, and a hierarchical design provides a flexible and portable fiamework suitable for different data-parallel SIMD architectures. 1 IMAGE-BASED VISUALIZATION Massively data-parallel architectures can realise close to peak performance on regularly structured image processing and viewing operations, allowing in some cases for real-time (or near real-time) interaction with modelling and viewing parameters [17]. A number of special architectures have been used for volume rendering [ 111. Polygon-based graphic algorithms pose problems of scalability, discretization independent of problem domain, and dependence on special purpose hardware for high performance [9]. Imageor pixel-based algorithms can be scalable with problem size, need not introduce geometrical artifacts and can be implemented on general purpose data-parallel computers. As a result, increases in model complexity (e.g. molecular modelling), empirical data generated from sensors (e.g. remote sensing and medical imaging) and inter* GPO Box 664, Canberra, ACT 2601, Australia Tel.: +616 275 0911 Fax: +616 257 1052 guy.vezina@csis.dit.csiro.au peter.fletcher@csis.dit.csiro.au phil.robertson@csis.dit.csiro.au Permission to copy without fee all or part of this material is granted provided that the copies are not made or distributed for direct commercial advantage, the ACM copyright notice and the title of the publication and its date appear, and notice is given that copying is by permission of the Association for Computing Machinery. To copy otherwise, or to republish, requires a fee and/or specific permission. 1992 Workshop on Volume Visualization/l 0/92/Boston, MA o 1992 ACM 0-89791-5293/92/0010/00003...

The application of perceptual color spaces to the display of remotely sensed imagery

1.50 action impose requirements that polygon-based systems often cannot satisfy. Image-based approaches are particularly well-suited to handling large multidimensional empirical data and the integration of computer vision, computer graphics and image processing 131. 2 DATA-PARALLEL VOLUME RENDERING The data-parallel algorithm achieves data access regularization by following the approach taken by Drebin&al.[4], which is a source for better efficiency in data access. Data-parallel geometrical transformations, including rotation and perspective, are applied to the data to localize projection rays within individual processing element memories. Once localization is completed, iso-surface rendering is computed using Levoy’s technique [12]. This consists of computing voxel opacities for iso-surface classification, computing Phong shading, and compositing along the viewing rays for the final view (See also [21] for an extensive discussion on volume rendering issues). The data-parallel geometrical transformation algorithm is based on separating multi-dimensional transformations into a series of one-dimensional operations that can be performed in parallel on regular data domains, providing an adequate level of parallelism for massively parallel architectures. A three-pass rotation algorithm is used, requiring shear/scale operations along orthogonal axes [lo]. Following volume rotation, perspective projection is performed in two passes by applying scaling to the scanlines. The rotation and perspective transformation can be combined and reduced to a four-pass shear/scale algorithm For a generic set of data-parallel geometric transformation tools for visualization applications, several issues must be considered: efficiency, flexibility, resampling artifacts, scalability and portability. 2.1 Requirements For interactive visualization, and for handling large volumetric data sets, efficiency is critical. F.vo classes of operations underlie imagebased transformations: the first is data processing comprising geometric or spatial transformation, resampling and associated filtering; the second is data handling, comprising data formatting and access according to algorithm and data-dependent requirements. Efficiency in handling large data sets on massively data-parallel machines relies heavily on two factors: regularizing data access, and reducing the data-value dependence of access requirements. Achieving the latter substantially eases the requirements for providing the former. Key to the approach is the common localization of domains which can be processed in parallel. The result is that some operations may be less efficient than they might otherwise have been independently, but that effectively the “lowest common denominator” domains guarantee that no operation can introduce severe penalties that dominate the results, either in data-dependent time complexity or in the potential introduction of artifacts

A methodology for scientific data visualisation: choosing representations based on a natural scene paradigm

The process of matching the type of information of interest with the ability of the different representation properties to convey this information is formalized in a generic framework. Visualization approaches are discussed, and the natural scene paradigm on which the methodology for choosing a representation is based is described. Data types and interpretation aims are explored. The use of the paradigm, the matching process, and implementation and display of the representation are described. The advantages of the methodology over ad hoc display approaches are examined. >

Fast Perspective Views of Images Using One-Dimensional Operations

An attempt is made to show how perceptually uniform color spaces can improve significantly the interpretability of displays and remotely sensed geoscientific imagery. A computational framework encompassing the mapping of data into perceptually uniform color spaces is presented, and practical application of this framework to various types of geophysical data is described. Applications include the depiction of informative data variables in specified lightness and saturation ranges, the effective utilization of chromatic contrast in multispectral data displays, and representations of more complex integrated data sets. >

Interactive shading for surface and volume visualization on graphics workstations

A methodology for guiding the choice of visual representations of data is presented. The methodology provides objective and directed display design facilities. Such facilities can guide interactive visualization design, generate standard visualizations automatically, and assess the extent to which chosen representations can convey the required information to data analysis. The methodology is based on objectively distinguishing the types of information conveyed by various visual representations and matching these to the intrinsic characteristics of data and to aims for its interpretation. This approach is directed toward developing a stronger theoretical basis for visualization in scientific computation. The methodology is developed using a natural scene paradigm in which data variables are represented by identifiable properties of realistic scenes.<<ETX>>

Terrain perspectives on a massively parallel SIMD computer

Generating arbitrary perspective views of images portraying 3D surfaces can involve extensive computation and data I/O time because of the problems in determining visibility, and performing hidden-point removal. Appropriate 1D transforms of an image can allow hidden-point removal and perspective projection to be performed on scan lines or columns of these transforms. Perspective view generation then reduces to a series of extremely fast 1D operations. As a result, exact perspective views of 3D surfaces of unlimited size can be generated very much more rapidly than hitherto possible, making this a feasible interactive tool in image analysis. Maximum speed is possible when entire data sets can be stored in random access memory (RAM). However, the scan-line nature of the algorithm also allows sequential processing of data stored on disk, and fast image transposition methods allow the generation of views of surfaces much larger than available memory.

Research issues in the foundations of visualization

Shading is an effective exploratory visualization tool widely used in scientific visualization. Interactive, or close to interactive, shading of images offers significant benefit, but is generally too computationally expensive for graphics workstations. A novel method for providing interactive diffuse and specular shading capability on low-cost graphics workstations is described. Application to digital elevation models, iso-surfaces in volumetric images, and color-coded aspect maps are illustrated and an analysis of artifacts, and of ways of minimizing artifacts, is given.<<ETX>>