Enhancing Visualization with Real-Time Frequency-based Transfer Functions

Abstract

Transfer functions have a crucial role in the understanding and visualization of 3D data. While research has scrutinized the possible uses of one and multi-dimensional transfer functions in the spatial domain, to our knowledge, no attempt has been done to explore transfer functions in the frequency domain. In this work we propose transfer functions for the purpose of frequency analysis and visualization of 3D data. Frequency-based transfer functions offer the possibility to discriminate signals, composed from different frequencies, to analyze problems related to signal processing, and to help understanding the link between the modulation of specific frequencies and their impact on the spatial domain. We demonstrate the strength of frequency-based transfer functions by applying them to medical CT, ultrasound and MRI data, physics data as well as synthetic seismic data. The interactive design of complex filters for feature enhancement can be a useful addition to conventional classification techniques.