April 14, 2013 5 Comments
Version : 1.3 – Living blog – First version was 15 avril 2013
This is the third post of a series about simulating rain and its effect on the world in game. As it is a pretty big post, I split it in two parts A and B:
Water drop 1 – Observe rainy world
Water drop 2a – Dynamic rain and its effects
Water drop 2b – Dynamic rain and its effects
Water drop 3a – Physically based wet surfaces
Water drop 3b – Physically based wet surfaces
Water drop 4a – Reflecting wet world
Water drop 4b – Reflecting wet world
Directly following the part A let’s continue with other rain effects:
Approximation for game
We have begun this post by studying the influence of water on lighting for wet surfaces. Then we have seen two real time implementations with analytic light for both optical phenomena which were inherited directly from the observation. They have some drawbacks, they miss an image based lighting implementation and their cost for in-game usage still a problem for XBOX360/PS3 game. In computer graphic there is a different path available to simulate optical phenomena other than changing the lighting model. We could simply create/edit/capture both wet and dry surfaces BRDF parameters (diffuse, specular, specular power…) with the same lighting model. This is not really a “simulation” as we know the final wet state of the surface but we are now able to render wet surfaces and to dynamically wet our game world. Simply interpolating between dry and wet BRDF parameters without changing the lighting model do the effect. Nevertheless this approach is stuck to the subsurface scattering events inside the wet material and its top, i.e the diffuse and specular of the wet surface itself. It will not allow to simulate the dual layering lighting we have study in part A when there is a thin layer of water on the top of the wet surface. I will discuss this point later.
The benefit is the simplicity of the process and we still compatible with any kind of lights: image based lighting and analytic. The drawback of requiring a dry and a wet set of BRDF parameters by surfaces is the time to author and store them. The wet lighting model approach required more instructions whereas this one require only few extra instructions (but this still two textures fetch for the blending). However in game development, doubling the storage in memory/disc space and the number of textures to author is prohibited. Hopefully we now know that’s we can express both wet and dry surfaces with the same lighting model, so maybe we can find a way to tweak the dry BRDF parameters to get an approximation of the wet’s one and thus avoid the inconvenient of storing and authoring new textures.
Almost all games I know chose to follow this BRDF parameters’ tweaking path : Stalker , Uncharted 2/3 (on the main character), Assassin’s creed 3 , Crysis 2/3, Metal Gear Solid V  etc… This is not surprising as the method seems simple and it fit very well with a deferred shading renderer: You can tweak dry BRDF parameters in the G-buffer without complicating the lighting systems. However the wet BRDF parameters generated by these games are either coarse or wrong approximation (in a physical sense, I am agree that’s visually the look can be Ok). Most use the same eye-calibrated factors to attenuate diffuse and boost specular (old fashion) on every wet surfaces of the scene regardless of material properties (roughness/smoothness, porosity, metalic/dielectric…). Assassin’s creed 3 even does an additional wrong step by changing the strength of the factor based on the type of rain. Remember from part A that under any type of rains a porous surface can be water saturated. This only depends on water precipitation volume and exposition time. A bit differently Tomb Raider : A survivor is born  use “dark light” to attenuate the light receive by the diffuse part of the wetted surfaces, the specular part is modified as other games. As they use lights to produce rain with a light prepass renderer, I think they intent to make up the missing of a diffuse parameter in the small G-Buffer with this method. Which again apply wrongly the same modification factors on all dry surfaces.
One of the purposes of the remainder of this section is to improve the BRDF wet parameters generation from the dry one. I want to highlight the benefit of PBR for this parameters generation. I will begin by talking about the tweaking of the diffuse (or subsurface scattering part) and the specular parameters for porous dielectric material then for other kind of materials. I will end with the effect of the thin layer of water which can accumulate above surfaces and the case of thick accumulated water like puddles.
Porous dielectric material
Disclaimer all color values I will talk about are in RGB linear space, not sRGB space. All graph show here are available in a Mathematica file at the end of this section.
We aim to found a factor which can be applied on a dry diffuse parameter to get a wet diffuse parameter and equivalent for the glossiness parameter. I will begin by an overview of previous works, they are all focus on rough dielectric material.
For asphalt in driving simulator, Nakamae et al  use a factor between 0.1 and 0.3 to attenuate the diffuse albedo and a factor of 5 to 10 to boost the specular (not PBR). As many other, they perform an empirical calibration for this coefficient without taking into account the properties of the surfaces.
 and  details the two optical theories that’s we see in this post (part A) which aim to explain the darkening of the albedo. We will call the model of  LD and the model of  TBM. I would advice that’s the albedo mention in this paper don’t match the diffuse albedo definition we use in computer graphic (i.e the diffuse color of a perfect lambertian surface), it contain some specular reflection. Both papers purpose a relationship between wet and dry albedo. They explain that’s the highest differences between wet and dry albedo occurs for surface in the middle range of dry albedo. Dark surfaces will tend to absorb more light on first contact with the surface, the contribution of internal reflections will be less important decreasing the effect of wetting. Bright surfaces will tend to reflect much more light than is absorbed by internal reflection also decreasing the effect of wetting. In both case the relationship between dry and wet albedo depends only on the index of refraction (IOR) of the surface, the IOR of the water and the dry albedo. The following graph is the wet albedo function of the dry albedo from the optical phenomena of  for an IOR of 1.5 for surface (common value for rough dielectric surface) and 1.33 for water. The red line is the dry albedo for comparison:
I found more readable to transform this graph to the fraction of wet / dry albedo function of albedo. This means the factor to apply to dry albedo to retrieve wet albedo:
They further show that the wet albedo is a non-linear function of dry albedo, with low albedos reduced more by wetting than high albedos. A consequence of this result (not explicitly stated in their paper) is that wet surface color is more saturated than dry surface color, because the wetting further exaggerates the differences in albedo for different wavelengths.