@inproceedings{Stalling:1995:FRI,
  optcitations = {},
  optorganization = {},
  author = {Detlev Stalling and Hans-Christian Hege},
  series = CGPACS,
  editor = {Robert Cook},
  localfile = {papers/Stalling.1995.FRI.pdf},
  address = {New York},
  optpublisher = {ACM Press/ACM SIGGRAPH},
  doi = {http://doi.acm.org/10.1145/218380.218448},
  optmonth = aug,
  citeseer = {http://citeseer.ist.psu.edu/stalling95fast.html},
  booktitle = SIGGRAPH95,
  optstatus = {OK},
  title = {{F}ast and {R}esolution {I}ndependent {L}ine {I}ntegral
           {C}onvolution},
  abstract = {Line Integral Convolution (LIC) is a powerful technique for
              generating striking images and animations from vector data.
              Introduced in 1993, themethod has rapidly foundmany application
              areas, ranging from computer arts to scientific visualization.
              Based upon locally filtering an input texture along a curved
              stream line segment in a vector field, it is able to depict
              directional information at high spatial resolutions. We present a
              new method for computing LIC images. It employs simple box filter
              kernels only and minimizes the total number of stream lines to be
              computed. Thereby it reduces computational costs by an order of
              magnitude compared to the original algorithm. Our method utilizes
              fast, error-controlled numerical integrators. Decoupling the
              characteristic lengths in vector field grid, input texture and
              output image, it allows computation of filtered images at
              arbitrary resolution. This feature is of significance in computer
              animation as well as in scientific visualization, where it can be
              used to explore vector data by smoothly enlarging structure of
              details. We also present methods for improved texture animation,
              again employing box filter kernels only. To obtain an optimal
              motion effect, spatial decay of correlation between intensities of
              distant pixels in the output image has to be controlled. This is
              achieved by blending different phase-shifted box filter animations
              and by adaptively rescaling the contrast of the output frames.},
  pages = {249--256},
  year = {1995},
}