Volume visualization and volume painting of large data sets
Master of Science
Volume visualization of large volume data sets is traditionally based on surface fitting algorithms. With recent advances in graphics computation and memory capabilities, direct volume rendering techniques to produce interactive volume rendering for large data sets have become feasible. We implement a custom texture based volume rendering algorithm that takes advantage of the advanced graphics hardware capabilities. Volume masking is used in volume visualization to visualize and distinguish the different regions of interest in a volume data set. Generating volume masks is a tedious and time intensive process. We propose a new approach for generating volume masks using a volume painting approach. The volume masking relies on a material mapping to map the different mask values in the volume mask to different regions and colors. We build a custom cross-platform visualization application to support interactive volume visualization and volume painting for large volume data sets.
Computer science; Applied sciences