Line integral convolution: Difference between revisions

Revision as of 15:02, 26 July 2025

Latest revision as of 02:13, 31 August 2025

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The final image will normally be colored in some way. Typically, some [[scalar field]] in <math>\Omega</math> (like the vector length) is used to determine the hue, while the grayscale LIC output determines the [[Lightness|brightness]].

Different choices of convolution kernels and random noise produce different textures; for example, [[pink noise]] produces a cloudy pattern where areas of higher flow stand out as smearing, suitable for weather visualization. Further refinements in the convolution can improve the quality of the image.<ref name="Weiskopf 2009">{{cite book |last1=Weiskopf |first1=Daniel |chapter-url=https://scholar.archive.org/detailswork/mathematicalfoun00mllet3e74cfmmjg6zcotlqqzy5dihq |title=Mathematical Foundations of Scientific Visualization, Computer Graphics, and Massive Data Exploration |publisher=[[Springer Science+Business Media|Springer]] |year=2009 |isbn=978-3-540-25076-0 |editor1-last=Möller |editor1-first=Torsten |series=Mathematics and Visualization |___location=Berlin, New York |pages=[https://archive.org/details/mathematicalfoun00mlle/page/n195 191]–211191–211 |chapter=Iterative Twofold Line Integral Convolution for Texture-Based Vector Field Visualization |citeseerx=10.1.1.66.3013 |doi=10.1007/b106657_10 |editor2-last=Hamann |editor2-first=Bernd |editor3-last=Russell |editor3-first=Robert D. |url-access=limited }}{{dead link|date=May 2024}}</ref>

===Programming description===