/* SPDX-License-Identifier: Apache-2.0 * Copyright 2011-2022 Blender Foundation */ #pragma once CCL_NAMESPACE_BEGIN typedef struct Bssrdf { SHADER_CLOSURE_BASE; Spectrum radius; Spectrum albedo; float roughness; float anisotropy; } Bssrdf; static_assert(sizeof(ShaderClosure) >= sizeof(Bssrdf), "Bssrdf is too large!"); /* Random Walk BSSRDF */ ccl_device float bssrdf_dipole_compute_Rd(float alpha_prime, float fourthirdA) { float s = sqrtf(3.0f * (1.0f - alpha_prime)); return 0.5f * alpha_prime * (1.0f + expf(-fourthirdA * s)) * expf(-s); } ccl_device float bssrdf_dipole_compute_alpha_prime(float rd, float fourthirdA) { /* Little Newton solver. */ if (rd < 1e-4f) { return 0.0f; } if (rd >= 0.995f) { return 0.999999f; } float x0 = 0.0f; float x1 = 1.0f; float xmid, fmid; constexpr const int max_num_iterations = 12; for (int i = 0; i < max_num_iterations; ++i) { xmid = 0.5f * (x0 + x1); fmid = bssrdf_dipole_compute_Rd(xmid, fourthirdA); if (fmid < rd) { x0 = xmid; } else { x1 = xmid; } } return xmid; } ccl_device void bssrdf_setup_radius(ccl_private Bssrdf *bssrdf, const ClosureType type, const float eta) { if (type == CLOSURE_BSSRDF_BURLEY_ID || type == CLOSURE_BSSRDF_RANDOM_WALK_FIXED_RADIUS_ID) { /* Scale mean free path length so it gives similar looking result to older * Cubic, Gaussian and Burley models. */ bssrdf->radius *= 0.25f * M_1_PI_F; } else { /* Adjust radius based on IOR and albedo. */ const float inv_eta = 1.0f / eta; const float F_dr = inv_eta * (-1.440f * inv_eta + 0.710f) + 0.668f + 0.0636f * eta; const float fourthirdA = (4.0f / 3.0f) * (1.0f + F_dr) / (1.0f - F_dr); /* From Jensen's `Fdr` ratio formula. */ Spectrum alpha_prime; FOREACH_SPECTRUM_CHANNEL (i) { GET_SPECTRUM_CHANNEL(alpha_prime, i) = bssrdf_dipole_compute_alpha_prime( GET_SPECTRUM_CHANNEL(bssrdf->albedo, i), fourthirdA); } bssrdf->radius *= sqrt(3.0f * (one_spectrum() - alpha_prime)); } } /* Christensen-Burley BSSRDF. * * Approximate Reflectance Profiles from * http://graphics.pixar.com/library/ApproxBSSRDF/paper.pdf */ /* This is a bit arbitrary, just need big enough radius so it matches * the mean free length, but still not too big so sampling is still * effective. */ #define BURLEY_TRUNCATE 16.0f #define BURLEY_TRUNCATE_CDF 0.9963790093708328f // cdf(BURLEY_TRUNCATE) ccl_device_inline float bssrdf_burley_fitting(float A) { /* Diffuse surface transmission, equation (6). */ return 1.9f - A + 3.5f * (A - 0.8f) * (A - 0.8f); } /* Scale mean free path length so it gives similar looking result * to Cubic and Gaussian models. */ ccl_device_inline Spectrum bssrdf_burley_compatible_mfp(Spectrum r) { return 0.25f * M_1_PI_F * r; } ccl_device void bssrdf_burley_setup(ccl_private Bssrdf *bssrdf) { /* Mean free path length. */ const Spectrum l = bssrdf_burley_compatible_mfp(bssrdf->radius); /* Surface albedo. */ const Spectrum A = bssrdf->albedo; Spectrum s; FOREACH_SPECTRUM_CHANNEL (i) { GET_SPECTRUM_CHANNEL(s, i) = bssrdf_burley_fitting(GET_SPECTRUM_CHANNEL(A, i)); } bssrdf->radius = l / s; } ccl_device float bssrdf_burley_eval(const float d, float r) { const float Rm = BURLEY_TRUNCATE * d; if (r >= Rm) return 0.0f; /* Burley reflectance profile, equation (3). * * NOTES: * - Surface albedo is already included into `sc->weight`, no need to * multiply by this term here. * - This is normalized diffuse model, so the equation is multiplied * by `2*pi`, which also matches `cdf()`. */ float exp_r_3_d = expf(-r / (3.0f * d)); float exp_r_d = exp_r_3_d * exp_r_3_d * exp_r_3_d; return (exp_r_d + exp_r_3_d) / (4.0f * d); } ccl_device float bssrdf_burley_pdf(const float d, float r) { if (r == 0.0f) { return 0.0f; } return bssrdf_burley_eval(d, r) * (1.0f / BURLEY_TRUNCATE_CDF); } /* Find the radius for desired CDF value. * Returns scaled radius, meaning the result is to be scaled up by d. * Since there's no closed form solution we do Newton-Raphson method to find it. */ ccl_device_forceinline float bssrdf_burley_root_find(float xi) { const float tolerance = 1e-6f; const int max_iteration_count = 10; /* Do initial guess based on manual curve fitting, this allows us to reduce * number of iterations to maximum 4 across the [0..1] range. We keep maximum * number of iteration higher just to be sure we didn't miss root in some * corner case. */ float r; if (xi <= 0.9f) { r = expf(xi * xi * 2.4f) - 1.0f; } else { /* TODO(sergey): Some nicer curve fit is possible here. */ r = 15.0f; } /* Solve against scaled radius. */ for (int i = 0; i < max_iteration_count; i++) { float exp_r_3 = expf(-r / 3.0f); float exp_r = exp_r_3 * exp_r_3 * exp_r_3; float f = 1.0f - 0.25f * exp_r - 0.75f * exp_r_3 - xi; float f_ = 0.25f * exp_r + 0.25f * exp_r_3; if (fabsf(f) < tolerance || f_ == 0.0f) { break; } r = r - f / f_; if (r < 0.0f) { r = 0.0f; } } return r; } ccl_device void bssrdf_burley_sample(const float d, float xi, ccl_private float *r, ccl_private float *h) { const float Rm = BURLEY_TRUNCATE * d; const float r_ = bssrdf_burley_root_find(xi * BURLEY_TRUNCATE_CDF) * d; *r = r_; /* h^2 + r^2 = Rm^2 */ *h = safe_sqrtf(Rm * Rm - r_ * r_); } ccl_device float bssrdf_num_channels(const Spectrum radius) { float channels = 0; FOREACH_SPECTRUM_CHANNEL (i) { if (GET_SPECTRUM_CHANNEL(radius, i) > 0.0f) { channels += 1.0f; } } return channels; } ccl_device void bssrdf_sample(const Spectrum radius, float xi, ccl_private float *r, ccl_private float *h) { const float num_channels = bssrdf_num_channels(radius); float sampled_radius; /* Sample color channel and reuse random number. Only a subset of channels * may be used if their radius was too small to handle as BSSRDF. */ xi *= num_channels; sampled_radius = 0.0f; float sum = 0.0f; FOREACH_SPECTRUM_CHANNEL (i) { const float channel_radius = GET_SPECTRUM_CHANNEL(radius, i); if (channel_radius > 0.0f) { const float next_sum = sum + 1.0f; if (xi < next_sum) { xi -= sum; sampled_radius = channel_radius; break; } sum = next_sum; } } /* Sample BSSRDF. */ bssrdf_burley_sample(sampled_radius, xi, r, h); } ccl_device_forceinline Spectrum bssrdf_eval(const Spectrum radius, float r) { Spectrum result; FOREACH_SPECTRUM_CHANNEL (i) { GET_SPECTRUM_CHANNEL(result, i) = bssrdf_burley_pdf(GET_SPECTRUM_CHANNEL(radius, i), r); } return result; } ccl_device_forceinline float bssrdf_pdf(const Spectrum radius, float r) { Spectrum pdf = bssrdf_eval(radius, r); return reduce_add(pdf) / bssrdf_num_channels(radius); } /* Setup */ ccl_device_inline ccl_private Bssrdf *bssrdf_alloc(ccl_private ShaderData *sd, Spectrum weight) { ccl_private Bssrdf *bssrdf = (ccl_private Bssrdf *)closure_alloc( sd, sizeof(Bssrdf), CLOSURE_NONE_ID, weight); if (bssrdf == NULL) { return NULL; } float sample_weight = fabsf(average(weight)); bssrdf->sample_weight = sample_weight; return (sample_weight >= CLOSURE_WEIGHT_CUTOFF) ? bssrdf : NULL; } ccl_device int bssrdf_setup(ccl_private ShaderData *sd, ccl_private Bssrdf *bssrdf, ClosureType type, const float ior) { int flag = 0; /* Add retro-reflection component as separate diffuse BSDF. */ if (bssrdf->roughness != FLT_MAX) { ccl_private PrincipledDiffuseBsdf *bsdf = (ccl_private PrincipledDiffuseBsdf *)bsdf_alloc( sd, sizeof(PrincipledDiffuseBsdf), bssrdf->weight); if (bsdf) { bsdf->N = bssrdf->N; bsdf->roughness = bssrdf->roughness; flag |= bsdf_principled_diffuse_setup(bsdf, PRINCIPLED_DIFFUSE_RETRO_REFLECTION); /* Ad-hoc weight adjustment to avoid retro-reflection taking away half the * samples from BSSRDF. */ bsdf->sample_weight *= bsdf_principled_diffuse_retro_reflection_sample_weight(bsdf, sd->I); } } /* Verify if the radii are large enough to sample without precision issues. */ int bssrdf_channels = SPECTRUM_CHANNELS; Spectrum diffuse_weight = zero_spectrum(); FOREACH_SPECTRUM_CHANNEL (i) { if (GET_SPECTRUM_CHANNEL(bssrdf->radius, i) < BSSRDF_MIN_RADIUS) { GET_SPECTRUM_CHANNEL(diffuse_weight, i) = GET_SPECTRUM_CHANNEL(bssrdf->weight, i); GET_SPECTRUM_CHANNEL(bssrdf->weight, i) = 0.0f; GET_SPECTRUM_CHANNEL(bssrdf->radius, i) = 0.0f; bssrdf_channels--; } } if (bssrdf_channels < SPECTRUM_CHANNELS) { /* Add diffuse BSDF if any radius too small. */ if (bssrdf->roughness != FLT_MAX) { ccl_private PrincipledDiffuseBsdf *bsdf = (ccl_private PrincipledDiffuseBsdf *)bsdf_alloc( sd, sizeof(PrincipledDiffuseBsdf), diffuse_weight); if (bsdf) { bsdf->N = bssrdf->N; bsdf->roughness = bssrdf->roughness; flag |= bsdf_principled_diffuse_setup(bsdf, PRINCIPLED_DIFFUSE_LAMBERT); } } else { ccl_private DiffuseBsdf *bsdf = (ccl_private DiffuseBsdf *)bsdf_alloc( sd, sizeof(DiffuseBsdf), diffuse_weight); if (bsdf) { bsdf->N = bssrdf->N; flag |= bsdf_diffuse_setup(bsdf); } } } /* Setup BSSRDF if radius is large enough. */ if (bssrdf_channels > 0) { bssrdf->type = type; bssrdf->sample_weight = fabsf(average(bssrdf->weight)) * bssrdf_channels; bssrdf_setup_radius(bssrdf, type, ior); flag |= SD_BSSRDF; } else { bssrdf->type = type; bssrdf->sample_weight = 0.0f; } return flag; } CCL_NAMESPACE_END