'How to interpolate between multiple biome height-maps?

For biome area distribution I combine perlin noise representing temperature, and moisture levels using voronoi cell distribution. The world is divided by some modulo and another perlin noise function to return a voronoi control point. The seams between biomes show. I thought a simple weight function will do:

An example of weight calculation for adjacent points

Orange point = the sample point which the weights will be calculated according to.

Using cellular noise (some kind of voronoi distribution similar to what I'm looking for, but doesn't blend different biomes):

An example of Cellular noise heightmap

To clarify vertex height:

float HeightAtPosition(float x, float z)
{
    //Returns an array containing information of all the adjacent biome 
    //control points(mainly their position and their biome type)
    BiomeControlPoint[] adjacentControlPoints = GetAdjacentBiomePoints(x, z);
    //Returns an array containing values between 0 and 1
    //Iputs: An array of all the adjacent biome points, a sample coordinate
    //Output: A float array containing the weight of each biome on the 
    //        coordinate(between 0 and 1)
    float[] weights = CalcWeights(adjacentControlPoints, new Vector2(x, z));
    float finalHeight = 0;
    for (int i = 0; i < adjacentControlPoints.Length; i++)
    {
        finalHeight += adjacentControlPoints[i] * weights[i];
    }
    return finalHeight;
}

A good solution if GetAdjacentBiomePoints(x, z) and CalcWeights(adjacentControlPoints, new Vector2(x, z)) were more performance efficient. Bilinear interpolation I don't understand.

c++sharpprocedural-generationheightmap


Solution 1:[1]

You could try a weighted voronoi diagram. My php implementation:https://tetramatrix.github.io/awvd/.

Solution 2:[2]

You could go the other way:

  • generate temperature and moisture levels for each pixel
  • generate how much each biome matches those values
    • precalculate strength of each biome as a 2d lookup table?
  • take the X best matches
  • normalize the strengths (sum is 1)
  • your a unique noise function combination is weighted sum of the X best biomes

Personally I work with gridmaps and interpolate the biome's valus from a small map with large cells to a large map with small cells. Interpolation is much easier there:

Sorry that it is java.

Sources

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Source: Stack Overflow

Solution Source
Solution 1 Micromega
Solution 2 Orchaldir

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