I discovered last year these tutorials by Jasper Flick on how to make and use noise in Unity, and a couple of terrain and particle use examples. They present the difference between value noise and gradient noise, how Perlin noise and simplex noise work, and among others how to use curl noise to control the flow of particles.
The order information is presented is well thought, although the intention might not be clear at first. Don’t let the beginner’s tutorial tone (“You’ll learn to: create and fill a texture;”, etc.) turn you away, as the series do a great job at detailing the concepts and algorithms in a simple manner yet without cutting corners like so many articles on the topic do (when they’re not blatantly wrong and go ahead calling a blurred noise “Perlin noise”). I thought I had a pretty good grasp of gradient noise already, but reading it gave me an even better understanding.
While at it, other resources on the topic include Ken Perlin’s GDC 1999 talk and his two pages paper Improving noise explaining why use a 5th order polynomial for interpolation (a function I’ve sometimes seen called “smootherStep”).
The compressive sensing blog Nuit-Blanche reports this publication: First-photon imaging. The technique allows to capture depth and (limited) reflectivity information using only a small number of photons (virtually in the dark).
Imagers that use their own illumination can capture 3D structure and reflectivity information. With photon-counting detectors, images can be acquired at extremely low photon fluxes. To suppress the Poisson noise inherent in low-flux operation, such imagers typically require hundreds of detected photons per pixel for accurate range and reflectivity determination. We introduce a low-flux imaging technique, called first-photon imaging, which is a computational imager that exploits spatial correlations found in real-world scenes and the physics of low-flux measurements. Our technique recovers 3D structure and reflectivity from the first detected photon at each pixel. We demonstrate simultaneous acquisition of sub-pulse duration range and 4-bit reflectivity information in the presence of high background noise. First-photon imaging may be of considerable value to both microscopy and remote sensing.