Integrating volume data analysis and rendering on distributed memory architectures

The ability to generate visual representations of data, and the ability to enhance data into a suitable form for the purpose of visual representation, form two key components in a scientific visualization system. By a visual representation we mean the ability to render the data, using visual cues, such that the important features are readily perceived by the user. By the ability to enhance data we mean the ability to apply transformations to the data so that salient features embedded in the data become discernible and quantifiable. The rendering of data, computer graphics, and the enhancement of data, image processing, have emerged over the last twenty years into separate scientific disciplines. However, in scientific visualization and other applications of empirical data interpretation, we are increasingly confronted with the need to combine both data rendering and data transformation capabilities under one system framework. This paper describes the design issues and implementation of a program for visualizing and enhancing volume data on distributed memory architectures. Our design is motivated by the desire to interactively view, transform, and interpret volume data acquired using seismic imaging techniques. Experimental results derived from an implementation on the Connection Machine CM-5 are described.