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Global Illumination using Photon Maps

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Global Illumination using Photon Maps

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  1. Global Illumination using Photon Maps

  2. Mainly using terms • Photon : emitting particle of energy from the light source • Photon Maps (store when hit surfaces) • Caustic (ex, light focused through a glass onto a table) • Monte Carlo Method & Ray Tracing

  3. Photon Map • when is the Photon Maps used ? • generate optimized sampling directions • reduce the number of shadow rays - use the shadow photon • render caustics • limit the number of reflections traced as the scene is rendered with distribution ray tracing

  4. Overview of the Method • Constructing the photon map • Store the incoming flux( photon )  estimate surface radiance at surface with arbitrary BRDF’s ★ radiance becomes lowers. • Rendering engine - Distribution ray tracer • Information of photon map is applied during rendering in two ways • Surfaces computation perform using importance sampling ( integrated with BRDF to provide optimized sampling directions )

  5. Pass 1 • Constructing the Photon Maps • Every time A Photon hits the surface it is stored within the photon maps (think the reflection between objects ... reflection repeat ) • Russian roulette is used – to determine whether the photon absorbed or reflected • The new direction of a reflected photon is computed using the BRDF of the surface

  6. Kinds of Photon maps • Caustic Photon Maps - It is created by emitting photons towards the specular objects in the scene and storing these as they hitdiffuse surfaces - Used only caustics • Global Photon Maps - It is created by emitting photons towards all objects - Used as a rough approximation of the light/flux within the scene - It is classified to optimize the rendering of shadows

  7. Shadow Photon • First intersection point – normal photon (low density and high energy ) • Second intersection point – shadow photon • Shadow photon - using reduce the number of shadow rays • Caustic photon • - high density and low energy The photons are stored in a balanced kd-tree

  8. Pass 2 • To draw image - Pixel radiance ( Monte Carlo ray Tracing) • The radiance per each ray – equals the surface radiance • Omit position and direction for clarity and express Lr as next

  9. Pass 2 • Equation is used to compute the radiance leaving a surface • contribution from the light sources, contribution from the light sources via specular reflection (caustic),, indirect soft illumination • accurate computation • approximate evaluation

  10. Getting two ways • accurate computation • Surface is seen directly by the eye or perhaps via a few specular reflections • The distance between the ray origin and the intersection point is below a small threshold value • approximate evaluation • The surface has been reflected diffusely • The weight of ray is low( contribution only little to the pixel radiance)

  11. Direct illumination (direct illumination) • Computed by sending shadow rays towards all light source to check for visibility • Specular Reflection (specular and highly glossy) • Computed using standard Monte Carlo ray tracing (importance sampling) • Caustics (caustic on diffuse and slightly glossy surface) • Using photon map information • Soft Indirect illumination • Using global Photon map – approximate evaluation • Importance sampling – accurate evaluation

  12. Image of Photon Map

  13. The next work • Monte Carlo Ray Tracing • Data structure of Photon Map • Estimating Radiance using the Photon map