Skip to main content
added 85 characters in body
Source Link

I suggest this aproach. Let fs(x,y) be your simplex noise function. Let's introduce a second function : f(x,y) = WIDTH * (1 - (X * X + Y * Y))f(x,y) = ((float)Math.Sin(((float)x/(float)WIDTH) * Math.PI) ) * ((float)Math.Sin(((float)y / (float)WIDTH) * Math.PI) ) or any function that rassemble the following and that gives values from 0 to 1:

enter image description here

at this point take your simplex noise fs(x,y) :

enter image description here

and multiply per f(x,y) you get something like this :

enter image description here

finaly apply a colorgradient to obtain something like :

enter image description here

I suggest this aproach. Let fs(x,y) be your simplex noise function. Let's introduce a second function : f(x,y) = WIDTH * (1 - (X * X + Y * Y)) or any function that rassemble the following and that gives values from 0 to 1:

enter image description here

at this point take your simplex noise fs(x,y) :

enter image description here

and multiply per f(x,y) you get something like this :

enter image description here

finaly apply a colorgradient to obtain something like :

enter image description here

I suggest this aproach. Let fs(x,y) be your simplex noise function. Let's introduce a second function : f(x,y) = ((float)Math.Sin(((float)x/(float)WIDTH) * Math.PI) ) * ((float)Math.Sin(((float)y / (float)WIDTH) * Math.PI) ) or any function that rassemble the following and that gives values from 0 to 1:

enter image description here

at this point take your simplex noise fs(x,y) :

enter image description here

and multiply per f(x,y) you get something like this :

enter image description here

finaly apply a colorgradient to obtain something like :

enter image description here

Source Link

I suggest this aproach. Let fs(x,y) be your simplex noise function. Let's introduce a second function : f(x,y) = WIDTH * (1 - (X * X + Y * Y)) or any function that rassemble the following and that gives values from 0 to 1:

enter image description here

at this point take your simplex noise fs(x,y) :

enter image description here

and multiply per f(x,y) you get something like this :

enter image description here

finaly apply a colorgradient to obtain something like :

enter image description here