@mastersthesis {eichelbaum2009,
	title = {Image Space Tensor Field Visualization Using a LIC-like Method},
	year = {2009},
	school = {Fakult{\"a}t f{\"u}r Mathematik und Informatik Universit{\"a}t Leipzig},
	type = {mastersDiploma Thesis},
	abstract = {Tensors are of great interest to many applications in engineering and in medical imaging, but a proper analysis and visualization remains challenging. Physics-based visualization of tensor fields has proven to show the main features of symmetric second-order tensor fields, while still displaying the most important information of the data, namely the main directions in medical diffusion tensor data using texture and additional attributes using color-coding, in a continuous representation. Nevertheless, its application and usability remains limited due to its computational expensive and sensitive nature. We introduce a novel approach to compute a fabric-like texture pattern from tensor fields on arbitrary non-selfintersecting surfaces that is motivated by image space line integral convolution (LIC). Our main focus lies on regaining three-dimensionality of the data under user interaction, such as rotation and scaling. We employ a multi-pass rendering approach to estimate proper modification of the LIC noise input texture to support the three-dimensional perception during user interactions.},
	author = {Eichelbaum, Sebastian}
}
