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569 行
21 KiB
569 行
21 KiB
#ifndef UNITY_IMAGE_BASED_LIGHTING_INCLUDED
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#define UNITY_IMAGE_BASED_LIGHTING_INCLUDED
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#include "CommonLighting.hlsl"
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#include "CommonMaterial.hlsl"
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#include "BSDF.hlsl"
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#include "Sampling.hlsl"
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// TODO: We need to change this hard limit!
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#ifndef UNITY_SPECCUBE_LOD_STEPS
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#define UNITY_SPECCUBE_LOD_STEPS 6
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#endif
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//-----------------------------------------------------------------------------
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// Util image based lighting
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//-----------------------------------------------------------------------------
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// The *approximated* version of the non-linear remapping. It works by
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// approximating the cone of the specular lobe, and then computing the MIP map level
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// which (approximately) covers the footprint of the lobe with a single texel.
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// Improves the perceptual roughness distribution.
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float PerceptualRoughnessToMipmapLevel(float perceptualRoughness, uint mipMapCount)
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{
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perceptualRoughness = perceptualRoughness * (1.7 - 0.7 * perceptualRoughness);
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return perceptualRoughness * mipMapCount;
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}
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float PerceptualRoughnessToMipmapLevel(float perceptualRoughness)
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{
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return PerceptualRoughnessToMipmapLevel(perceptualRoughness, UNITY_SPECCUBE_LOD_STEPS);
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}
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// The *accurate* version of the non-linear remapping. It works by
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// approximating the cone of the specular lobe, and then computing the MIP map level
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// which (approximately) covers the footprint of the lobe with a single texel.
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// Improves the perceptual roughness distribution and adds reflection (contact) hardening.
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// TODO: optimize!
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float PerceptualRoughnessToMipmapLevel(float perceptualRoughness, float NdotR)
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{
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float m = PerceptualRoughnessToRoughness(perceptualRoughness);
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// Remap to spec power. See eq. 21 in --> https://dl.dropboxusercontent.com/u/55891920/papers/mm_brdf.pdf
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float n = (2.0 / max(FLT_EPSILON, m * m)) - 2.0;
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// Remap from n_dot_h formulation to n_dot_r. See section "Pre-convolved Cube Maps vs Path Tracers" --> https://s3.amazonaws.com/docs.knaldtech.com/knald/1.0.0/lys_power_drops.html
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n /= (4.0 * max(NdotR, FLT_EPSILON));
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// remap back to square root of real roughness (0.25 include both the sqrt root of the conversion and sqrt for going from roughness to perceptualRoughness)
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perceptualRoughness = pow(2.0 / (n + 2.0), 0.25);
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return perceptualRoughness * UNITY_SPECCUBE_LOD_STEPS;
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}
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// The inverse of the *approximated* version of perceptualRoughnessToMipmapLevel().
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float MipmapLevelToPerceptualRoughness(float mipmapLevel)
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{
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float perceptualRoughness = saturate(mipmapLevel / UNITY_SPECCUBE_LOD_STEPS);
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return saturate(1.7 / 1.4 - sqrt(2.89 / 1.96 - (2.8 / 1.96) * perceptualRoughness));
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}
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// Ref: "Moving Frostbite to PBR", p. 69.
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float3 GetSpecularDominantDir(float3 N, float3 R, float roughness, float NdotV)
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{
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float a = 1.0 - roughness;
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float s = sqrt(a);
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#ifdef USE_FB_DSD
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// This is the original formulation.
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float lerpFactor = (s + roughness) * a;
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#else
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// TODO: tweak this further to achieve a closer match to the reference.
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float lerpFactor = (s + roughness) * saturate(a * a + lerp(0.0, a, NdotV * NdotV));
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#endif
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// The result is not normalized as we fetch in a cubemap
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return lerp(N, R, lerpFactor);
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}
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//-----------------------------------------------------------------------------
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// Anisotropic image based lighting
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//-----------------------------------------------------------------------------
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// To simulate the streching of highlight at grazing angle for IBL we shrink the roughness
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// which allow to fake an anisotropic specular lobe.
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// Ref: http://www.frostbite.com/2015/08/stochastic-screen-space-reflections/ - slide 84
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float AnisotropicStrechAtGrazingAngle(float roughness, float perceptualRoughness, float NdotV)
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{
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return roughness * lerp(saturate(NdotV * 2.0), 1.0, perceptualRoughness);
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}
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// ----------------------------------------------------------------------------
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// Importance sampling BSDF functions
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// ----------------------------------------------------------------------------
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void SampleGGXDir(float2 u,
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float3 V,
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float3x3 localToWorld,
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float roughness,
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out float3 L,
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out float NdotL,
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out float NdotH,
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out float VdotH,
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bool VeqN = false)
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{
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// GGX NDF sampling
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float cosTheta = sqrt((1.0 - u.x) / (1.0 + (roughness * roughness - 1.0) * u.x));
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float phi = TWO_PI * u.y;
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float3 localH = SphericalToCartesian(phi, cosTheta);
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NdotH = cosTheta;
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float3 localV;
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if (VeqN)
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{
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// localV == localN
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localV = float3(0.0, 0.0, 1.0);
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VdotH = NdotH;
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}
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else
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{
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localV = mul(V, transpose(localToWorld));
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VdotH = saturate(dot(localV, localH));
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}
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// Compute { localL = reflect(-localV, localH) }
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float3 localL = -localV + 2.0 * VdotH * localH;
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NdotL = localL.z;
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L = mul(localL, localToWorld);
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}
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// ref: http://blog.selfshadow.com/publications/s2012-shading-course/burley/s2012_pbs_disney_brdf_notes_v3.pdf p26
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void SampleAnisoGGXDir(float2 u,
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float3 V,
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float3 N,
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float3 tangentX,
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float3 tangentY,
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float roughnessT,
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float roughnessB,
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out float3 H,
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out float3 L)
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{
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// AnisoGGX NDF sampling
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H = sqrt(u.x / (1.0 - u.x)) * (roughnessT * cos(TWO_PI * u.y) * tangentX + roughnessB * sin(TWO_PI * u.y) * tangentY) + N;
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H = normalize(H);
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// Convert sample from half angle to incident angle
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L = 2.0 * saturate(dot(V, H)) * H - V;
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}
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// weightOverPdf return the weight (without the diffuseAlbedo term) over pdf. diffuseAlbedo term must be apply by the caller.
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void ImportanceSampleLambert(float2 u,
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float3x3 localToWorld,
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out float3 L,
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out float NdotL,
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out float weightOverPdf)
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{
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float3 localL = SampleHemisphereCosine(u.x, u.y);
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NdotL = localL.z;
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L = mul(localL, localToWorld);
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// Importance sampling weight for each sample
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// pdf = N.L / PI
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// weight = fr * (N.L) with fr = diffuseAlbedo / PI
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// weight over pdf is:
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// weightOverPdf = (diffuseAlbedo / PI) * (N.L) / (N.L / PI)
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// weightOverPdf = diffuseAlbedo
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// diffuseAlbedo is apply outside the function
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weightOverPdf = 1.0;
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}
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// weightOverPdf return the weight (without the Fresnel term) over pdf. Fresnel term must be apply by the caller.
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void ImportanceSampleGGX(float2 u,
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float3 V,
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float3x3 localToWorld,
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float roughness,
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float NdotV,
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out float3 L,
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out float VdotH,
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out float NdotL,
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out float weightOverPdf)
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{
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float NdotH;
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SampleGGXDir(u, V, localToWorld, roughness, L, NdotL, NdotH, VdotH);
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// Importance sampling weight for each sample
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// pdf = D(H) * (N.H) / (4 * (L.H))
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// weight = fr * (N.L) with fr = F(H) * G(V, L) * D(H) / (4 * (N.L) * (N.V))
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// weight over pdf is:
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// weightOverPdf = F(H) * G(V, L) * (L.H) / ((N.H) * (N.V))
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// weightOverPdf = F(H) * 4 * (N.L) * V(V, L) * (L.H) / (N.H) with V(V, L) = G(V, L) / (4 * (N.L) * (N.V))
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// Remind (L.H) == (V.H)
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// F is apply outside the function
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float Vis = V_SmithJointGGX(NdotL, NdotV, roughness);
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weightOverPdf = 4.0 * Vis * NdotL * VdotH / NdotH;
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}
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// weightOverPdf return the weight (without the Fresnel term) over pdf. Fresnel term must be apply by the caller.
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void ImportanceSampleAnisoGGX(float2 u,
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float3 V,
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float3x3 localToWorld,
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float roughnessT,
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float roughnessB,
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float NdotV,
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out float3 L,
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out float VdotH,
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out float NdotL,
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out float weightOverPdf)
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{
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float3 tangentX = localToWorld[0];
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float3 tangentY = localToWorld[1];
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float3 N = localToWorld[2];
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float3 H;
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SampleAnisoGGXDir(u, V, N, tangentX, tangentY, roughnessT, roughnessB, H, L);
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float NdotH = saturate(dot(N, H));
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// Note: since L and V are symmetric around H, LdotH == VdotH
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VdotH = saturate(dot(V, H));
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NdotL = saturate(dot(N, L));
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// Importance sampling weight for each sample
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// pdf = D(H) * (N.H) / (4 * (L.H))
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// weight = fr * (N.L) with fr = F(H) * G(V, L) * D(H) / (4 * (N.L) * (N.V))
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// weight over pdf is:
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// weightOverPdf = F(H) * G(V, L) * (L.H) / ((N.H) * (N.V))
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// weightOverPdf = F(H) * 4 * (N.L) * V(V, L) * (L.H) / (N.H) with V(V, L) = G(V, L) / (4 * (N.L) * (N.V))
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// Remind (L.H) == (V.H)
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// F is apply outside the function
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// For anisotropy we must not saturate these values
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float TdotV = dot(tangentX, V);
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float BdotV = dot(tangentY, V);
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float TdotL = dot(tangentX, L);
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float BdotL = dot(tangentY, L);
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float Vis = V_SmithJointGGXAniso(TdotV, BdotV, NdotV, TdotL, BdotL, NdotL, roughnessT, roughnessB);
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weightOverPdf = 4.0 * Vis * NdotL * VdotH / NdotH;
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}
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// ----------------------------------------------------------------------------
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// Pre-integration
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// ----------------------------------------------------------------------------
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// Ref: Listing 18 in "Moving Frostbite to PBR" + https://knarkowicz.wordpress.com/2014/12/27/analytical-dfg-term-for-ibl/
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float4 IntegrateGGXAndDisneyFGD(float3 V, float3 N, float roughness, uint sampleCount = 4096)
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{
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float NdotV = saturate(dot(N, V));
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float4 acc = float4(0.0, 0.0, 0.0, 0.0);
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// Add some jittering on Hammersley2d
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float2 randNum = InitRandom(V.xy * 0.5 + 0.5);
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float3x3 localToWorld = GetLocalFrame(N);
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for (uint i = 0; i < sampleCount; ++i)
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{
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float2 u = frac(randNum + Hammersley2d(i, sampleCount));
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float VdotH;
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float NdotL;
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float weightOverPdf;
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float3 L; // Unused
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ImportanceSampleGGX(u, V, localToWorld, roughness, NdotV,
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L, VdotH, NdotL, weightOverPdf);
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if (NdotL > 0.0)
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{
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// Integral is
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// 1 / NumSample * \int[ L * fr * (N.L) / pdf ] with pdf = D(H) * (N.H) / (4 * (L.H)) and fr = F(H) * G(V, L) * D(H) / (4 * (N.L) * (N.V))
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// This is split in two part:
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// A) \int[ L * (N.L) ]
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// B) \int[ F(H) * 4 * (N.L) * V(V, L) * (L.H) / (N.H) ] with V(V, L) = G(V, L) / (4 * (N.L) * (N.V))
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// = \int[ F(H) * weightOverPdf ]
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// Recombine at runtime with: ( f0 * weightOverPdf * (1 - Fc) + f90 * weightOverPdf * Fc ) with Fc =(1 - V.H)^5
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float Fc = pow(1.0 - VdotH, 5.0);
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acc.x += (1.0 - Fc) * weightOverPdf;
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acc.y += Fc * weightOverPdf;
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}
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// for Disney we still use a Cosine importance sampling, true Disney importance sampling imply a look up table
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ImportanceSampleLambert(u, localToWorld, L, NdotL, weightOverPdf);
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if (NdotL > 0.0)
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{
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float3 H = normalize(L + V);
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float LdotH = dot(L, H);
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float disneyDiffuse = DisneyDiffuseNoPI(NdotV, NdotL, LdotH, RoughnessToPerceptualRoughness(roughness));
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acc.z += disneyDiffuse * weightOverPdf;
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}
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}
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return acc / sampleCount;
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}
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uint GetIBLRuntimeFilterSampleCount(uint mipLevel)
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{
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uint sampleCount = 0;
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switch (mipLevel)
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{
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case 1: sampleCount = 21; break;
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case 2: sampleCount = 34; break;
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#ifdef SHADER_API_MOBILE
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case 3: sampleCount = 34; break;
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case 4: sampleCount = 34; break;
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case 5: sampleCount = 34; break;
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case 6: sampleCount = 34; break; // UNITY_SPECCUBE_LOD_STEPS
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#else
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case 3: sampleCount = 55; break;
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case 4: sampleCount = 89; break;
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case 5: sampleCount = 89; break;
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case 6: sampleCount = 89; break; // UNITY_SPECCUBE_LOD_STEPS
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#endif
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}
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return sampleCount;
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}
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// Ref: Listing 19 in "Moving Frostbite to PBR"
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float4 IntegrateLD(TEXTURECUBE_ARGS(tex, sampl),
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TEXTURE2D(ggxIblSamples),
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float3 V,
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float3 N,
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float roughness,
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float index, // Current MIP level minus one
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float lastMipLevel,
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float invOmegaP,
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uint sampleCount, // Must be a Fibonacci number
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bool prefilter,
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bool usePrecomputedSamples)
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{
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float3x3 localToWorld = GetLocalFrame(N);
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#ifndef USE_KARIS_APPROXIMATION
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float NdotV = 1; // N == V
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float preLambdaV = GetSmithJointGGXPreLambdaV(1, roughness);
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#endif
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// Bias samples towards the mirror direction to reduce variance.
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// This will have a side effect of making the reflection sharper.
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// Ref: Stochastic Screen-Space Reflections, p. 67.
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const float bias = 0.5 * roughness;
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float3 lightInt = float3(0.0, 0.0, 0.0);
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float cbsdfInt = 0.0;
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for (uint i = 0; i < sampleCount; ++i)
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{
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float3 L;
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float NdotL, NdotH, VdotH;
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bool isValid;
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if (usePrecomputedSamples)
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{
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float3 localL = LOAD_TEXTURE2D(ggxIblSamples, uint2(i, index)).xyz;
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L = mul(localL, localToWorld);
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NdotL = localL.z;
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isValid = true;
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}
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else
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{
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float2 u = Fibonacci2d(i, sampleCount);
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u.x = lerp(u.x, 0.0, bias);
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SampleGGXDir(u, V, localToWorld, roughness, L, NdotL, NdotH, VdotH, true);
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isValid = NdotL > 0.0;
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}
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float mipLevel;
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if (!prefilter) // BRDF importance sampling
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{
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mipLevel = 0;
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}
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else // Prefiltered BRDF importance sampling
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{
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// Use lower MIP-map levels for fetching samples with low probabilities
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// in order to reduce the variance.
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// Ref: http://http.developer.nvidia.com/GPUGems3/gpugems3_ch20.html
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//
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// pdf = D * NdotH * jacobian, where jacobian = 1.0 / (4* LdotH).
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//
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// Since L and V are symmetric around H, LdotH == VdotH.
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// Since we pre-integrate the result for the normal direction,
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// N == V and then NdotH == LdotH. Therefore, the BRDF's pdf
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// can be simplified:
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// pdf = D * NdotH / (4 * LdotH) = D * 0.25;
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//
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// - OmegaS : Solid angle associated with the sample
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// - OmegaP : Solid angle associated with the texel of the cubemap
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float omegaS;
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if (usePrecomputedSamples)
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{
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omegaS = LOAD_TEXTURE2D(ggxIblSamples, uint2(i, index)).w;
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}
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else
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{
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float pdf = D_GGX(NdotH, roughness) * 0.25;
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// TODO: check the accuracy of the sample's solid angle fit for GGX.
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omegaS = rcp(sampleCount) / pdf;
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}
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// invOmegaP is precomputed on CPU and provide as a parameter of the function
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// float omegaP = FOUR_PI / (6.0 * cubemapWidth * cubemapWidth);
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mipLevel = 0.5 * log2(omegaS * invOmegaP);
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}
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if (isValid)
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{
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// Bias the MIP map level to compensate for the importance sampling bias.
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// This will blur the reflection.
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// TODO: find a more accurate MIP bias function.
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mipLevel = lerp(mipLevel, lastMipLevel, bias);
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// TODO: use a Gaussian-like filter to generate the MIP pyramid.
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float3 val = SAMPLE_TEXTURECUBE_LOD(tex, sampl, L, mipLevel).rgb;
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// The goal of this function is to use Monte-Carlo integration to find
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// X = Integral{Radiance(L) * CBSDF(L, N, V) dL} / Integral{CBSDF(L, N, V) dL}.
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// Note: Integral{CBSDF(L, N, V) dL} is given by the FDG texture.
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// CBSDF = F * D * G * NdotL / (4 * NdotL * NdotV) = F * D * G / (4 * NdotV).
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// PDF = D * NdotH / (4 * LdotH).
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// Weight = CBSDF / PDF = F * G * LdotH / (NdotV * NdotH).
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// Since we perform filtering with the assumption that (V == N),
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// (LdotH == NdotH) && (NdotV == 1) && (Weight == F * G).
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// Therefore, after the Monte Carlo expansion of the integrals,
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// X = Sum(Radiance(L) * Weight) / Sum(Weight) = Sum(Radiance(L) * F * G) / Sum(F * G).
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#ifndef USE_KARIS_APPROXIMATION
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float F = 1; // The choice of the Fresnel factor does not appear to affect the result
|
|
float V = V_SmithJointGGX(NdotL, NdotV, roughness, preLambdaV);
|
|
float G = V * /* 4 * */ NdotL * NdotV; // 4 cancels out
|
|
lightInt += F * G * val;
|
|
cbsdfInt += F * G;
|
|
#else
|
|
// Use the approximation of Brian Karis from "Real Shading in Unreal Engine 4":
|
|
// Weight ≈ NdotL.
|
|
lightInt += NdotL * val;
|
|
cbsdfInt += NdotL;
|
|
#endif
|
|
}
|
|
}
|
|
|
|
return float4(lightInt / cbsdfInt, 1.0);
|
|
}
|
|
|
|
// Searches the row 'j' containing 'n' elements of 'haystack' and
|
|
// returns the index of the first element greater or equal to 'needle'.
|
|
uint BinarySearchRow(uint j, float needle, TEXTURE2D(haystack), uint n)
|
|
{
|
|
uint i = n - 1;
|
|
float v = LOAD_TEXTURE2D(haystack, uint2(i, j)).r;
|
|
|
|
if (needle < v)
|
|
{
|
|
i = 0;
|
|
|
|
for (uint b = 1 << firstbithigh(n - 1); b != 0; b >>= 1)
|
|
{
|
|
uint p = i | b;
|
|
v = LOAD_TEXTURE2D(haystack, uint2(p, j)).r;
|
|
if (v <= needle) { i = p; } // Move to the right.
|
|
}
|
|
}
|
|
|
|
return i;
|
|
}
|
|
|
|
float4 IntegrateLD_MIS(TEXTURECUBE_ARGS(envMap, sampler_envMap),
|
|
TEXTURE2D(marginalRowDensities),
|
|
TEXTURE2D(conditionalDensities),
|
|
float3 V,
|
|
float3 N,
|
|
float roughness,
|
|
float invOmegaP,
|
|
uint width,
|
|
uint height,
|
|
uint sampleCount,
|
|
bool prefilter)
|
|
{
|
|
float3x3 localToWorld = GetLocalFrame(N);
|
|
|
|
float2 randNum = InitRandom(V.xy * 0.5 + 0.5);
|
|
|
|
float3 lightInt = float3(0.0, 0.0, 0.0);
|
|
float cbsdfInt = 0.0;
|
|
|
|
/*
|
|
// Dedicate 50% of samples to light sampling at 1.0 roughness.
|
|
// Only perform BSDF sampling when roughness is below 0.5.
|
|
const int lightSampleCount = lerp(0, sampleCount / 2, saturate(2.0 * roughness - 1.0));
|
|
const int bsdfSampleCount = sampleCount - lightSampleCount;
|
|
*/
|
|
|
|
// The value of the integral of intensity values of the environment map (as a 2D step function).
|
|
float envMapInt2dStep = LOAD_TEXTURE2D(marginalRowDensities, uint2(height, 0)).r;
|
|
// Since we are using equiareal mapping, we need to divide by the area of the sphere.
|
|
float envMapIntSphere = envMapInt2dStep * INV_FOUR_PI;
|
|
|
|
// Perform light importance sampling.
|
|
for (uint i = 0; i < sampleCount; i++)
|
|
{
|
|
float2 s = frac(randNum + Hammersley2d(i, sampleCount));
|
|
|
|
// Sample a row from the marginal distribution.
|
|
uint y = BinarySearchRow(0, s.x, marginalRowDensities, height - 1);
|
|
|
|
// Sample a column from the conditional distribution.
|
|
uint x = BinarySearchRow(y, s.y, conditionalDensities, width - 1);
|
|
|
|
// Compute the coordinates of the sample.
|
|
// Note: we take the sample in between two texels, and also apply the half-texel offset.
|
|
// We could compute fractional coordinates at the cost of 4 extra texel samples.
|
|
float u = saturate((float)x / width + 1.0 / width);
|
|
float v = saturate((float)y / height + 1.0 / height);
|
|
float3 L = ConvertEquiarealToCubemap(u, v);
|
|
|
|
float NdotL = saturate(dot(N, L));
|
|
|
|
if (NdotL > 0.0)
|
|
{
|
|
float3 val = SAMPLE_TEXTURECUBE_LOD(envMap, sampler_envMap, L, 0).rgb;
|
|
float pdf = (val.r + val.g + val.b) / envMapIntSphere;
|
|
|
|
if (pdf > 0.0)
|
|
{
|
|
// (N == V) && (acos(VdotL) == 2 * acos(NdotH)).
|
|
float NdotH = sqrt(NdotL * 0.5 + 0.5);
|
|
|
|
// *********************************************************************************
|
|
// Our goal is to use Monte-Carlo integration with importance sampling to evaluate
|
|
// X(V) = Integral{Radiance(L) * CBSDF(L, N, V) dL} / Integral{CBSDF(L, N, V) dL}.
|
|
// CBSDF = F * D * G * NdotL / (4 * NdotL * NdotV) = F * D * G / (4 * NdotV).
|
|
// Weight = CBSDF / PDF.
|
|
// We use two approximations of Brian Karis from "Real Shading in Unreal Engine 4":
|
|
// (F * G ≈ NdotL) && (NdotV == 1).
|
|
// Weight = D * NdotL / (4 * PDF).
|
|
// *********************************************************************************
|
|
|
|
float weight = D_GGX(NdotH, roughness) * NdotL / (4.0 * pdf);
|
|
|
|
lightInt += weight * val;
|
|
cbsdfInt += weight;
|
|
}
|
|
}
|
|
}
|
|
|
|
// Prevent NaNs arising from the division of 0 by 0.
|
|
cbsdfInt = max(cbsdfInt, FLT_MIN);
|
|
|
|
return float4(lightInt / cbsdfInt, 1.0);
|
|
}
|
|
|
|
#endif // UNITY_IMAGE_BASED_LIGHTING_INCLUDED
|