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4

You can blend noise together easily, the concept is pretty simple. You essentially loop through each noise value, and perform an operation on the data, and then save the result. It is also a good idea to normalize this data as it makes it easier to use for future operations. Here is a simple container class to hold resulting noise data: public class ...


3

Here: perlin.lerp(v, perlin.lerp(u, perlin.grad(self[AB + 2], x , y , z - 1), This should have AA + 2 instead.


9

You will need to learn how the terms Octave, Persistence, Frequency, and Lacunarity are used. What you have is a good first step, it looks just like noise should. The basic idea is that you need to combine multiple noise sources into one result to achieve the final look. This combination can be something simple like addition, but you can take many ...


-2

Thanks to some of the above comments I did find my answer. I forgot to post my answer, but I thought I would go ahead and add it for anyone who is curious. I recommend looking at the original algorithm and also the above mentioned link to explain the general idea. I chose to use three-dimensional Perlin Noise (by Ken Perlin originally). This is a smooth ...


0

Honestly, I think trying to do this with the CPU is just way more work than it's worth. This is the kind of texture operation GPUs were made to simplify & accelerate for us. This animation was created using this shader code: Shader "Unlit/Rorschach" { Properties { _MainTex ("Texture", 2D) = "white" {} _BlackLevel("Black ...


-3

Yes, and it appears to be straight forward. You need to create perlin noise then apply a filter that would take that noise and if its below a certain threshold return black, otherwise return white. Then you can invert the image along the x and y axes to get the "rorshasch" look. The actual implementation is beyond the scope of the site, so heres a link to a ...



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