Enhancing Visualization with Frequency-based Transfer Functions

Transfer functions have a crucial role in the understanding and visualization of 3D data in the spatial domain. While exhaustive research has scrutinized the possible uses of one or multi-dimensional transfer functions in the visualization of the data in the spatial domain, to our knowledge no attempt has been done in the exploration of the use of transfer functions in the frequency domain. In this work we propose the use of 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 our technique by applying the frequency-based transfer function to synthetic and real-world medical data. The interactivity of the proposed framework allows the creation of complex filters and can also be used for structure or feature enhancement.