Files
test2/intern/cycles/kernel/closure/bssrdf.h
Weizhen Huang 543bf28fb1 Refactor: renamed I -> wi, omega_in -> wo in Cycles
wi is the viewing direction, and wo is the illumination direction. Under this notation, BSDF sampling always samples from wi and outputs wo, which is consistent with most of the papers and mitsuba. This order is reversed compared with PBRT, although PBRT also traces from the camera.
2023-01-17 18:07:13 +01:00

354 lines
9.9 KiB
C++

/* 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->wi);
}
}
/* 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