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Most current
implementations of fog in games use layered alpha images. This technique,
however, does not bare significantly resemblance to how fog actually composites
in real life, since density of the fog from the viewer is not modeled
in any way.
A Simple Model
of Fog
In order to create fog effects in a game, it is first necessary to create
an analytical model that bears some resemblance to the mechanics of real
fog. Fog is a cloud of water vapor consisting of millions of tiny particles
floating in space. Incoming light is scattered and emitted back into the
scene. This model is too complex to render in real time, and so a few
assumptions and restrictions must be made. The following is a similar
model to what is used in depth fog.
The first and most important assumption, common to many real time fog
implementations, is that incoming light at each particle is constant.
That is, one particle of fog located at one end of a fog volume and another
particle are receiving the same amount of incoming light.
The next related assumption is that each particle of fog emits the same
amount of light, and in all directions. This, of course, implies that
a fog's density remains fixed. These two assumptions mean that, given
a spherical volume of fog, equal light is emitted in all directions.
Using these assumptions, a model of fog can be defined. If a ray is cast
back from a pinhole camera through the scene - the amount of fog that
contributes to the color of that ray is the sum of all the light along
the ray's path. In other words, the amount of contributing light is equal
to the area of fog between the camera and the point in the screen. The
light of the incoming ray, however, was partially absorbed by the fog
itself, thus reducing its intensity.
So, the
proposed model of fog is (done for each color channel):
Intensity
of Pixel = (1-Ls*As)*(Ir) + Le*Ae*If.
Ls =
Amount of Light absorbed by fog.
Le = Amount of Light emitted by fog.
As = Area of fog absorbing light
Ae = Area of fog emitting light
Ir = Intensity of the light coming from the scene.
If = Intensity of the light coming from the fog.
Since the
area of fog emitting light is the same for the area of fog absorbing light,
and the assumption is made that the amount of light emitted is the same
percentage as absorbed, then this equal simplifies to:
Intensity of Pixel = (1- A*L)*(Ir) + L*A*If.
L = Amount
of light absorbed/emitted by fog (fog density)
A = Area of fog.
Ir = Intensity of the light coming from the scene.
If = Intensity of the light coming from the fog.
If this
is a per pixel operation, then the incoming light is already computed
by rendering the scene as it would normally appear. An analytical way
of thinking of this problem is: The amount a pixel changes to the fog
color is proportional to the amount of fog between the camera and the
pixel. This, of course, is the same model that is used in distance fog.
Thus, the problem is reduced to determining the amount of fog between
the camera and the pixel being rendered.
Determining Fog Depth at each pixel location
Standard Depth fog uses the Z (or w) value as the density of fog. This
works well, but limits the model to omnipresent fog. That is, the camera
is always in fog, and there is (Save a definable sphere around the camera)
an even amount of fog at all points in the scene.
Of course, this does not work well (or at all) for such effects as a ground
fog, and this technique cannot be used for interesting volumetric lighting.
An alternative way to create fog is to model a polygonal hull that represents
the fog, and to compute the area of fog for each pixel rendered on the
scene. At first glance, this seams impossibly complex. Computing volume
area typically involves complex integration.
However, the shaft of fog along a ray can be closely approximated subtracting
the w depth a ray enters a fog volume from the w depth of the point it
leaves the volume, and multiplying by some constant. (Mathematically,
this is a simple application of a form of Stoke's theorem, where all but
2 of the terms cancel since the flux is constant in the interior).
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