This is documentation for Mathematica 7, which was
based on an earlier version of the Wolfram Language.

# LineIntegralConvolutionPlot

 LineIntegralConvolutionPlot[{{vx, vy}, image}, {x, xmin, xmax}, {y, ymin, ymax}] generates a line integral convolution plot of image convolved with the vector field {vx, vy} as a function of x and y. LineIntegralConvolutionPlot[{vx, vy}, {x, xmin, xmax}, {y, ymin, ymax}]generates a line integral convolution plot of white noise with the vector field {vx, vy}.
• LineIntegralConvolutionPlot creates a rasterized version of image, then does a line integral convolution of each pixel according to the field defined by the vector function {vx, vy}.
 AspectRatio 1 ratio of height to width BoxRatios Automatic effective 3D box ratios for simulated lighting ColorFunction Automatic how to color background densities ColorFunctionScaling True whether to scale arguments to ColorFunction EvaluationMonitor None expression to evaluate at every function evaluation LineIntegralConvolutionScale Automatic length of convolution along streamlines Frame True whether to draw a frame around the plot FrameTicks Automatic frame tick marks LightingAngle None effective angle for simulated lighting Method Automatic methods to use for the plot PerformanceGoal \$PerformanceGoal aspects of performance to try to optimize PlotRange {Full,Full} range of x, y values to include PlotRangePadding Automatic how much to pad the range of values RasterSize Automatic the pixel width of the rasterized image WorkingPrecision MachinePrecision precision to use in internal computations
• If image is not specified, or is not already rasterized, a raster is created with a size specified by the RasterSize option.
• With a setting other than , simulated lighting is used, with the height at each point being taken to be determined from the norm of the vector field.
Plot the line integral convolution for a vector field starting with a random background:
Use an imported image:
Plot the line integral convolution for a vector field starting with a random background:

Use an imported image:
 Out[1]=
 Out[2]=
 Scope   (6)
Transform an image by a line integral convolution:
Use an image directly as input:
Plot a field image and overlaid streamlines:
Plot a field image and overlaid field vectors:
Plot a field image and overlaid vectors at random positions:
Show the effects of an increasing line integral convolution scale:
 Applications   (3)
Use a line integral convolution plot as a background for an interactive demo:
Display characteristics of several different types of linear planar systems:
Show the local direction of the gradient of a function along with its level curves:
Use the image as a background for investigating different unconstrained optimization methods:
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