单声道噪声与Perlin噪声 [英] Simplex noise vs Perlin noise

问题描述

我想知道为什么在Simplex问世后，Perlin噪音仍然如此受欢迎。单一噪声是由Ken Perlin自己制作的，并且它假设接管了他的旧算法，这种算法对于更高的尺寸和更好的质量（没有可见的伪像）来说很慢。

I would like to know why Perlin noise is still so popular today after Simplex came out. Simplex noise was made by Ken Perlin himself and it was suppose to take over his old algorithm which was slow for higher dimensions and with better quality (no visible artifacts).

Simplex噪音在2001年出现，在这10年中，我只看到人们谈论Perlin噪音，当涉及到为地形生成高度图，创建程序纹理等等。

Simplex noise came out in 2001 and over those 10 years I've only seen people talk of Perlin noise when it comes to generating heightmaps for terrains, creating procedural textures, et cetera.

任何人都可以帮助我，Simplex噪音是否存在一些缺点？我听说有传言说Perlin噪音在1D和2D噪音方面更快，但我不知道它是否真实。

Could anyone help me out, is there some downside of Simplex noise? I heard rumors that Perlin noise is faster when it comes to 1D and 2D noise, but I don't know if it's true or not.

谢谢！

推荐答案

如果没有损坏，请不要修理它。

"If it ain't broke, don't fix it."

看看你是否能找到告诉你为什么Simplex更好的人。 它更快，并扩展到多个维度和单一噪声试图降低更高维度噪声函数的复杂性是我发现的。我们大多数人都在2或3个维度工作，如果我们足够幸运能够随着时间的推移做些事情，那么我们大多数都会工作4个。

See if you can find anyone telling you why Simplex is better. "It's faster and extends to multiple dimensions" and "simplex noise attempts to reduce the complexity of higher dimensional noise functions" were what I found. Most of us work in 2 or 3 dimensions, maybe 4 if we're lucky enough to be doing something with time.

我认为可以说它有足够的空间Perlin的实时使用太慢而无法处理，对于大多数用途而言，标准的Perlin噪声就足够了。在预渲染中（例如在电影行业中使用），时间并不重要，因为渲染效果仍然很慢;在实时仿真中，我们有足够的方法来减少持续处理的范围，你不太可能每隔几毫秒或毫秒产生大量的噪声图 - 这只是基本的实时优化。

I think its fair to say there is little enough real-time usage of Perlin that is too slow to handle, that for most purposes standard Perlin noise is sufficient. In pre-renderings (such as used in the movie industry) time isn't really important since renderings are slow anyway; and in real-time simulations, we have enough ways to reduce the scope of ongoing processing that it's unlikely you're going to be generating massive noise maps every few nano/milliseconds -- that's just basic real-time optimisation.

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