Rendering using Linearly Transformed Cosines

Is it possible to get Ray Traced Effects in Rasterized Framework or at the least minimal Ray Tracing

Code Link The fonts used in the images are from my favourite graphics card company Nvidia and the colors used in the renders reflect my predilection towards the other graphics competitors (green > blue > red.)

Brief Into

Rasterization is widely used method for rendering geometries. To achieve photo-realistic effects it makes suitable approximations, takes scene awarness into account. Many works have tried incorporating the photo-realisim using required approximation namely Spherical Harmonics Lighting.

One of the complex scenario to reproduce in a rasterized setup is as follows:

An polygonal area light on top of the scene

Simple Path tracing can be used to get the above result using the equation provided below. I have used Nvidia Optix 7+ to achieve it.

\[\mathcal{L}_{o} = \mathcal{L}_{e}(x, \omega_o) + \int_{\Omega} f_{r}(x, \omega_i, \omega_o)\mathcal{L}_{i}(x, \omega_i)(\omega_{i} \cdot n)d\omega_{i}\]

As the light source present in the scene is an area light(scene is shown below). The work of [Arvo 1995 Siggraph] provides a line-integral based approach for finding the contibution of the area-light in the setting of direct lighting.

Scene visualization (only Albedo)

Stage 1: LTC’s(Linearly Transfomed Cosines)

Fairly recent, work LTC [Heitz et al. 2016 Siggraph] has formualted a BRDF fitting approch to obtain the area light contributions without the tracing rays at the run-time. The renders looks very similar to that of a ray-traced. Specifically in the regions of highlights.

Albeit the Lossing shadows LTC's faithfully produces the effects of ray-tracing.

Brief mathematical Explaination of how it is done?

(Why not detailled? Just to spare the jargon!!!! Isn't that obvious)

The approach of LTC(Linearly Transformed Cosines) relies on a transformation obtained from the fitting of Cosine samples to that of a GGX.(OK! How does that help?)

Well, once you have such fitting rather than shooting rays into scene and obtaining radiance values like we do in the case of Ray-tracing, we just keep a record of the light in the scene. Now, for every point to be rederered, we project the area lights on to the point’s hemisphere, apply a transformation using the matricies fitted using LTC. The transfromed matrix can be used in conjunction with the Linear Integral(Boundary Integral) to obtain light’s contribution effect.

Stage 2: OK! How to address the lost Visibility?

Look at the picture below.

We can observe that, despite being occluded by the torous(Donut shaped object in blue) the blocks under it do not have shadow like we have in ray-traced result.

To obtain the contribution of shadows, the work of Ratio Estimator[Heitz et al 2018] sparsely shoots rays and evaluates of the intergral with and without taking Visiblity into account.

What does that mean???

\[L = \underbrace{\int_{\Omega}BRDF \times Light}_{unshadowed\ analytical\ evaluation\ using\ LTC} \times \underbrace{\frac{\int_{\Omega}BRDF \times Light \times Visibility}{\int_{\Omega}BRDF \times Light}}_{Stochastic\ Evaluation\ with\ denoise\ of\ Numerator\ and\ denominator}\]

The above equations says: The first-term unshadowed analytical evaluation using LTC is calcualted via LTCs using prior approch of LTC [Heitz et al. 2016] the rest of terms are obtained via a performing sparse ray-traced estimate using MIS(Multiple Importance Sampling) of Light and BRDF-GGX(NDF). The second-term numerator is evaluated taking the visibility into account and the denominator does not take visibility into account. The calculation of both terms are using same set of sampled rays.

BOTH NEEDS TO DENOISED INDIVIDUALLY AND DIVIDED!

The left figure is NUMERATOR of the second term in the above equation which. (Observe the shadows) The right one is DENOMINATOR which disregards visibility.

In order to obtain the results of direct illumination in the setting of LTC Ratio Estimator suggests denoising of individual terms of numerator and denominator. I have used Optix 7.5 deep learning based denoiser instead of Bilater filter.

The left figure is Denoised Numerator of the second term in the above equation. (Observe the shadows) The right one is disregarding the shadows while denoised.

We multiply first term with the second term and get the following result.

The left figure is Direct illumination obtained using Optix 7. (Observe the shadows) The second is from the Ratio Estimator.

Visually we can notice a difference. It is a good approximation of ray-traced direct illumination.

Stage 3: Is the problem solved??????

Not exactly! What about GI?

I built the Stage 1 and Stage 2 till now using Optix 7.5 and I am currently trying figure out ways to incorporate GI - Global Illumination in this setting.

References:

[Arvo 1995 Siggraph]: Applications of Irradiance Tensors to the Simulation of Non-Lambertian Phenomena.
[Heitz et al. 2016]: Real-Time Polygonal-Light Shading with Linearly Transformed Cosines
[Heitz et al. 2018 I3D]: Combining Analytic Direct Illumination and Stochastic Shadows