Spray Rendering: A New Framework for Visualization

We propose a new framework for doing scientific visualization that allows the users to freely explore their data set. This framework uses a metaphorical abstraction of a virtual can of spray paint that can be used to render data sets and make them visible. Different cans of spray paint may be used to color the data differently. Different types of spray paint may also be used to highlight different features in the data set. To achieve this, individual paint particles are endowed with intelligent behavior. This idea offers several advantages over existing methods: (1) it generalizes the current techniques of surface, volume and flow visualization under one coherent framework; (2) it works with regular and irregular grids as well as sparse and dense data sets; (3) it allows selective progressive refinement and can be implemented on parallel architectures in a straight forward manner; (4) it is modular, extensible and provides scientists with the flexibility for exploring relationships in their data sets in natural and artistic ways.