## Silky Smooth Perlin Noise Surface

At work I’ve recently been generating viewsheds over DTED sets. Earlier this week I was asked to give an informal presentation on what I was doing. I wanted some terrain that demonstrated some key features, such as vision being occluded by hills of varying heights. Rather than search through the available DTED files for something good, I opted for generating my own terrain, using an old trick of mine: my noise “cloud” generator. That’s a lesson in the usefulness of maintaining a blog. The useful things you learn and create are easy to revisit years later!

I generated some noise, looked at it with `surf()`

, and repeated until
I found something useful. (*Update June 2012:* the function is called
`perlin()`

but it’s not actually Perlin noise.)

```
m = perlin(1024);
surf(m);
```

The generated terrain is really quite rough, so I decided to smooth it out by convolving it with a 2-dimensional Gaussian kernel.

```
k = fspecial('gaussian', 9);
ms = conv2(m, k, 'same');
```

It still wasn’t smooth enough. So I repeated the process a bit,

```
for i = 1:10
ms = conv2(ms, k, 'same');
end
```

Perfect! I used that for my presentation. However, I was having fun
and decided to experiment more with this. I filtered it again another
1000 times and generated a `surf()`

plot with a high-resolution
colormap — the default colormap size caused banding.

```
colormap(copper(1024));
surf(ms, 'EdgeAlpha', 0);
axis('equal');
```

It produced this beautiful result!

I think it looks like a photograph from a high-powered microscope, or maybe the turbulent surface of some kind of creamy beverage being stirred.

At work when I need something Matlab-ish, I use Octave about half the
time and Matlab the other half. In this case, I was using
Matlab. Octave doesn’t support the `EdgeAlpha`

property, nor the
`viewshed()`

function that I needed for my work. Matlab currently
makes much prettier plots than Octave.

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