Simon's Tech Blog

Photon Mapping Part 1

Introduction

In this generation of computer graphics, global illumination (GI) is an important technique which calculate indirect lighting within a scene. Photon mapping is one of the GI technique using particle tracing to compute images in offline rendering. Photon mapping is an easy to implement technique, so I choose to learn it and my target is to bake light map storing indirect diffuse lighting information using the photon map. Photon mapping consists of 2 passes: photon map pass and render pass, which will be described below.

Photon Map Pass

In this pass, photons will be casted into the scene from the position of light source. Each photon store packet of energy. When photon hits a surface of the scene, the photon will either be reflected (either diffusely or specularly), transmitted or absorbed, which is determined by Russian roulette.

Photons are traced in the scene to simulate the light transportation

This hit event represents the incoming energy of that surface and will be stored in a k-d tree (known as photon map) for looking up in the render pass. Each hit event would store the photon energy, the incoming direction and the hit position.

However, it is more convenient to store radiance than storing energy in photon because when using punctual light source(e.g. point light), it is hard to compute the energy emits given the light source radiance. So I use the method described in Physically Based Rendering, a weight of radiance is stored in each photon:

When a photon hits a surface, the probability of being reflected in a new random direction used in Russian roulette is:

This probability equation is chosen because photon will have a higher chance of being reflected if it is brighter. If the photon is reflected, its radiance will be updated to:

And the photon will continue to trace in the newly reflected direction.

Render pass

In render pass, the direct and indirect lighting is computed separately. The direction lighting is computed using ray tracing.

Direct light only

The indirect lighting is computed by sampling from the photon map. When calculating the indirect lighting in a given position(in this case, the shading pixel), we can locate N nearby photons in photon map to estimate the incoming radiance using kernel density estimation. A kernel function need to satisfy the conditions:

I use the Simpson's kernel(also known as Silverman's second order kernel) suggested in the book Physically Based Rendering:

Then the density can be computed using kernel estimator for N samples within a distance d (i.e. the distance of the photon that is the most far away in the N samples):

Then the reflected radiance at the shading position can be computed with:

However, the result showing some circular artifact:

Using the photon map directly for indirect diffuse
light would show artifact

To tackle this problem, either increase the number of photon to a very high number, or we can perform a final gather step. In the final gather step, we shoot a number of final gather rays from the pixel that we are shading in random direction over the hemisphere of the shading point.

Final gather rays are casted from every shading position

When final gather ray hit another surface, then the photon map is queried just like before and the reflected radiance from this surface will be the incoming radiance of the shading pixel. Using Monte Carlo integration, the reflected radiance at the shading pixel can be calculated by sampling the final gather rays. Here is the final result:

Direct light + Indirect light, with final gather

Indirect light only, with final gather

Conclusion

In this post, the steps to implement photon map is briefly described. It is a 2 passes approach with the photon map pass building a photon map as kd-tree representing the indirect lighting data and the render pass use the photon map to compute the final image. In next part, I will describe how to make use of the photon map to bake light map for real time application.

References

A Practical Guide to Global Illumination using Photon Maps: http://nameless.cis.udel.edu/class_data/cg/jensen_photon_mapping_tutorial.pdf
Physically Based Rendering: http://www.pbrt.org/

Software Rasterizer Part 2

Introduction
Continue with the previous post, after filling the triangle with scan line or half-space algorithm, we also need to interpolate the vertex attributes across the triangle so that we can have texture coordinates or depth on every pixel. However we cannot directly interpolate those attributes in screen space because projection transform after perspective division is not an affine transformation (i.e. after transformation, the mid-point of the line segment is no longer the mid-point), this will result in some distortion and this artifact is even more noticeable when the triangle is large:

interpolate in screen space

perspective correct interpolation

Condition for linear interpolation
When interpolating the attributes in a linear way, we are saying that given a set of vertices, vi (where i is any integer>=0) with a set of attributes ai (such as texture coordinates),
we have a function mapping a vertex to the corresponding attributes, i.e.

f(vi)= ai

Say, to interpolate a vertex inside a triangle in a linear way, the function f need to have the following properties:

f(t0 *v0 + t1 *v1 + t2 *v2 ) = t0 * f(v0) + t1 * f(v1) + t2 * f(v2)

, for any t0, t1, t2 where t0 + t1 + t2=1

which means that we can calculate the interpolated attributes using the same weight ti used for interpolating vertex position. For functions having the above properties, those functions will be an affine function with the following form:

f(x)= Ax + b

, where A is a matrix, x and b are vector

Depth interpolation
When a vertex is projected from view space to normalized device coordinates(NDC), we will have the following relation (ratio of the triangles) between the view space and NDC space:

substitute equation 1 and 2 into the plane equation of the triangle lies on:

So, 1/zview is an affine function of xndc and yndc which can be interpolated linearly across the screen space (the transform from NDC space to screen space is a linear transform).

Attributes interpolation
In last section, we know how to interpolate the depth of a pixel linearly in screen space, the next problem is to interpolate the vertex attributes(e.g. texture coordinates). In view space, we know that those attributes can be interpolated linearly, so those attributes can be calculated by an affine function with the vertex position as parameters e.g.

Similar to interpolate depth, substitute equation 1 and 2 into the above equation:

Therefore, u/zview is an another affine function of xndc and yndc which can be interpolated linearly across the screen space. Hence we can interpolating u linearly by first interpolate 1/zview and u/zview across screen space, and then divide them per pixel.

The last problem...

Now, we know that we can interpolate the view space depth and vertex attributes linearly across screen space. But during the rasterization state, we only have vertices in homogenous coordinates (vertices are transformed by the projection matrix already), how can we get the zview to do the perspective correct interpolation?
Consider the projection matrix (I use D3D one, but the same for openGL):

After transforming the vertex position, the w-coordinate will be the view space depth!

i.e. whomogenous = zview

And look at the matrix again and consider the transformed z-coordinates, it will in a form of:

After transforming to the NDC,

So the depth value can be directly interpolated using zNDC for depth test.

Demo
A javascript demo to rasterize the triangles is provided(although not optimized...). And the source code can be downloaded here.

Render Type: Depth Only Texture Only Lighting Only Texture + Lighting	Model: Box Duck
Perspective Correct Interpolation:	Rotate Model

Conclusion
In this post, the steps to linear interpolate the vertex in screen space is described. And for rasterizing the depth buffer only (e.g. for occlusion), the depth value can be linearly interpolated directly with the z coordinate in NDC space which is even simpler.

References
[1] http://www.lysator.liu.se/~mikaelk/doc/perspectivetexture/
[2] http://www.gamedev.net/topic/581732-perspective-correct-depth-interpolation/
[3] http://chrishecker.com/Miscellaneous_Technical_Articles
[4] http://en.wikipedia.org/wiki/Affine_transformation

Software Rasterizer Part 1

Introduction
Software rasterizer can be used for occlusion culling, some games such as Killzone 3 use this to cull objects. So I decided to write one by myself. The steps are first to transform vertices to homogenous coordinates, clip the triangles to the viewport and then fill the triangles with interpolated parameters. Note that the clipping process should be done in homogenous coordinates before the perspective division, otherwise lots of the extra work are need to clip the triangles properly and this post will explain why clipping should be done before the perspective division.

Points in Homogenous coordinates
In our usual Cartesian Coordinate system, we can represent any points in 3D space in the form of (X, Y, Z). While in Homogenous coordinates, a redundant component w is added which resulting in a form of (x, y, z, w). Multiplying any constant (except zero) to that 4-components vector is still representing the same point in homogenous coordinates. To convert a homogenous point back to our usual Cartesian Coordinate, we would multiply a point in homogenous coordinates so that the w component is equals to one:

(x, y, z, w) -> (x/w , y/w , z/w, 1) -> (X, Y, Z)

In the following figure, we consider the x-w plane, a point (x, y, z, w) is transformed back to the usual Cartesian Coordinates (X, Y, Z) by projecting onto the w=1 plane:

figure 1. projecting point to w=1 plane

The interesting point comes when the w component is equals to zero. Imagine the w component is getting smaller and smaller, approaching zero, the coordinates of point (x/w , y/w , z/w, 1) will getting larger and larger. When w is equals to zero, we can represent a point at infinity.

Line Segments in Homogenous coordinates
In Homogenous coordinates, we still can represent a line segment between two points P0= (x0, y0, z0, w0) and P1= (x1, y1, z1, w1) in parametric form:

L= P0 + t * (P1-P0), where t is within [0, 1]

Then we can get a line having the shape:

figure 2. internal line segment

The projected line on w=1 is called internal line segment in the above case.
But what if the coordinates of P0 and P1 having the coordinates where w0 < 0 and w1 > 0 ?

figure 3. external line segment

In this case, it will result in the above figure, forming an external line segment. It is because the homogenous line segment have the form L= P0 + t * (P1-P0), when moving the parameter from t=0 to t= 1, since w0 < 0 and w1 > 0, there exist a point on the homogenous line where w=0. This point is at infinity when projected to the w=1 plane, resulting the projected line segment joining P0 and P1 passes through the point at infinity, forming an external line segment.

The figure below shows how points are transformed before and after perspective projection and divided by w:

figure 4. region mapping

The blue line shows the viewing frustum, nothing unusual for the region in front of the eye. The unusual things are the points behind the eye. After perspective transformation and projected to w=1 plane, those points are transformed in front of the eye too. So for line segment with one point in front of the eye and the other behind the eye, it would be transformed to the external line segment after the perspective division.

Triangles in Homogenous coordinates

In the last section, we know that there are internal and external line segments after the perspective division, we also have internal and external triangles. The internal triangles are the one that we usually sees. The external triangles must be formed by 1 internal line segment and 2 external line segments:

figure 5. external triangle

In the above figure, the shaded area represents the external triangle formed by the points P0, P1 and P2. This kind of external triangles may appear after the perspective projection transform. And this happens in our real world too:

an external triangle in real world

the full triangle of the left photo

In the left photo, it shows an external triangle with one of the triangle vertex far behind the camera while the right photo shows the full view of the triangle and the cross marked the position of the camera where the left photo is taken.

Triangles clipping
To avoid the case of external triangles, lines/triangles should be clipped in homogenous coordinates before divided by the w-component. The homogenous point (x, y, z, w) will be tested with the following inequalities:

(-w <= x <= w) && ------ inequality. 1

(-w <= y <= w) && ------ inequality. 2

(-w <= z <= w ) && ------ inequality. 3
w > 0 ------ inequality. 4

(The z clipping plane inequality is 0 <= z <= w in the case for D3D, it depends on how the normalized device coordinates are defined.) Clipping by inequality 1,2,3 will effectively clip all points that with w < 0 because if w < 0, say w = -3:

3 <= x <= -3 => 3 <= -3

which is impossible. But the point (0, 0, 0, 0) is still satisfy the first 3 inequalities and forming external cases, so inequality 4 is added. Consider a homogenous line with one end as (0, 0, 0, 0), it will equals to:

L= (0, 0, 0, 0) + t * [ (x, y, z, w) - (0, 0, 0, 0) ] = t * (x, y, z, w)

which represent only a single point in homogenous coordinates. So triangle (after clipped by inequality 1, 2, 3) having one or two vertices with w=0 will result in either a line or a point which can be discarded. Hence, after clipping, no external triangles will be produced when dividing by w-component. To clip a triangle against a plane, the triangle may result in either 1 or 2 triangles depends on whether there are 1 or 2 vertex outside the clipping plane:

figure 6. clipping internal triangles

Then the clipped triangles can be passed to the next stage to be rasterized either by a scan line algorithm or by a half-space algorithm.

Below is the clipping result of an external triangles with 1 vertex behind the camera.