MonteCarloRaytraycer
The famous rendering equation was first introduced in 1986 by James Kajiya and later refined to bidirectional path tracing by Lafortune. Its numerical solution is approximated by the path tracing algorithm, also referred to as Monte Carlo raytracing. Essentially, the algorithm integrates over all illuminance arriving at a surface point. All such paths in the scene are generated by recursion as with each ray-surface intersection the algorithm performs illuminance gathering over a hemispherical region. This sampling region is a construct of propabilistic generation of new rays in accordance with the Bidirectional Random Distribution Function (BRDF) provided by the surface. The BRDF can be thought of as a four dimensional function that has the ability to modify the hemispherical region to favour certain directions to simulate surfaces that are not fully opaque. As the level of recursion and number of samples increases the repeated sampling will eventually cause the average of samples to converge towards the analytic solution.
Install / Use
/learn @micma909/MonteCarloRaytraycerREADME
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MonteCarloRaytraycer
The famous rendering equation was first introduced in 1986 by James Kajiya and later refined to bidirectional path tracing by Lafortune. Its numerical solution is approximated by the path tracing algorithm, also referred to as Monte Carlo raytracing. Essentially, the algorithm integrates over all illuminance arriving at a surface point. All such paths in the scene are generated by recursion as with each ray-surface intersection the algorithm performs illuminance gathering over a hemispherical region. This sampling region is a construct of propabilistic generation of new rays in accordance with the Bidirectional Random Distribution Function (BRDF) provided by the surface. The BRDF can be thought of as a four dimensional function that has the ability to modify the hemispherical region to favour certain directions to simulate surfaces that are not fully opaque. As the level of recursion and number of samples increases the repeated sampling will eventually cause the average of samples to converge towards the analytic solution.
