Deep dive into the topic of procedural noise from a unique perspective. We explore its origins, properties, applications, and more!
Resources for further exploration:
- [1], [2] - Great starting point if you want to explore ideas of the frequency domain. Both monographs are focused on computer vision. However, those foundations apply to a wide range of fields. Besides notes, there are recorded lectures, and Professor Nayar is an excellent teacher!
- [3] - This entire book is dedicated to procedural generation and contains much information about noise, among other interesting topics. However, it’s mathematics isn’t “self-contained“.
- [4] - This book also introduces the frequency domain in the context of computer graphics. It also contains the foundations of mathematics that you need to understand those concepts deeper. If you’re comfortable with at least high-school math, this book is an excellent starting point.
- [5] - Formal introduction to procedural noise and ways we evaluate it - a bit tough read, though :)
[1] Image Processing I,
Shree K. Nayar,
Monograph FPCV-1-4, First Principles of Computer Vision,
Columbia University, New York, Mar. 2022
[2] Image Processing II,
Shree K. Nayar,
Monograph FPCV-1-5, First Principles of Computer Vision,
Columbia University, New York, Mar. 2022
[3] Texturing and Modeling: A Procedural Approach (3rd. ed.).
David S. Ebert, F. Kenton Musgrave, Darwyn Peachey, Ken Perlin, and Steven Worley. 2002. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA.
[4] Steve Marschner and Peter Shirley. 2016. Fundamentals of Computer Graphics, Fourth Edition (4th. ed.). A. K. Peters, Ltd., USA.
[5] Lagae, A., Lefebvre, S., Cook, R., DeRose, T., Drettakis, G., Ebert, D.S., Lewis, J.P., Perlin, K. and Zwicker, M. (2010), A Survey of Procedural Noise Functions. Computer Graphics Forum, 29: 2579-2600.
Links (amazon links are affiliate):
- [1], [2]: , @firstprinciplesofcomputerv3258
- [3]:
- [4]:
- [5]:
Timestamps:
0:00 - Introduction
1:00 - Randomness
2:39 - Noise
3:54 - Obtaining Noise
5:01 - Coin Flip Noise
6:50 - Brownian Noise
8:28 - Terrain Noise
10:47 - Sinusoidal Waves
13:12 - Making Noise With Sinusoidal Waves
15:36 - Frequency Decomposition
16:53 - Utilising Frequency Domain
18:03 - White Noise
19:41 - Frequency Filtering
21:09 - Evaluating Our Noise
22:36 - Generating Random Numbers
24:17 - Hash Function
25:55 - Value Noise
28:31 - Fractal Noise
Special thanks to:
- Tobias Rittig
- @waffleboytom
- Adam Piskala
- Kristian Kubenka
- Martmists
Besides being a passion project, this video is my take on the #SoME3 competition.
Soundtrack by Ben Elson - I’ve used tracks from his album Orthosie
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I’ve used some assets from digital libraries. Music, SFX comes from Epidemic Sound, and some real-life shots come from Envato Elements.
Epidemic Sound: (affiliate)