cessen/psychopath
1
0
Fork 0
Code Issues 1 Pull Requests Projects Releases Wiki Activity

Use independent Sobol sequences for different sets of dimensions.

Browse Source 
This reduces correlation artifacts, while preserving good convergence
for the most part.
This commit is contained in:
Nathan Vegdahl 2020-04-22 18:38:05 +09:00
parent aecff883ab
commit 22b7151919
2 changed files with 17 additions and 9 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

22
src/renderer.rs
View File

@ -374,7 +374,7 @@ pub struct LightPath {
sampling_seed: u32, sampling_seed: u32,
pixel_co: (u32, u32), pixel_co: (u32, u32),
sample_number: u32, // Which sample in the LDS sequence this is. sample_number: u32, // Which sample in the LDS sequence this is.
dim_offset: Cell<u32>, dim_offset: u32,
time: f32, time: f32,
wavelength: f32, wavelength: f32,
@ -407,7 +407,7 @@ impl LightPath {
sampling_seed: sampling_seed, sampling_seed: sampling_seed,
pixel_co: pixel_co, pixel_co: pixel_co,
sample_number: sample_number, sample_number: sample_number,
dim_offset: Cell::new(6), dim_offset: 0,
time: time, time: time,
wavelength: wavelength, wavelength: wavelength,
@ -430,9 +430,14 @@ impl LightPath {
) )
} }
fn next_lds_samp(&self) -> f32 { fn next_lds_sequence(&mut self) {
let dimension = self.dim_offset.get(); self.dim_offset = 0;
self.dim_offset.set(dimension + 1); self.sampling_seed += 1;
}
fn next_lds_samp(&mut self) -> f32 {
let dimension = self.dim_offset;
self.dim_offset += 1;
get_sample( get_sample(
dimension, dimension,
self.sample_number, self.sample_number,
@ -481,6 +486,7 @@ impl LightPath {
self.light_attenuation /= self.closure_sample_pdf; self.light_attenuation /= self.closure_sample_pdf;
// Prepare light ray // Prepare light ray
self.next_lds_sequence();
let light_n = self.next_lds_samp(); let light_n = self.next_lds_samp();
let light_uvw = ( let light_uvw = (
self.next_lds_samp(), self.next_lds_samp(),
@ -599,6 +605,7 @@ impl LightPath {
// Sample closure // Sample closure
let (dir, filter, pdf) = { let (dir, filter, pdf) = {
self.next_lds_sequence();
let u = self.next_lds_samp(); let u = self.next_lds_samp();
let v = self.next_lds_samp(); let v = self.next_lds_samp();
closure.sample( closure.sample(
@ -701,10 +708,7 @@ fn get_sample(dimension: u32, i: u32, pixel_co: (u32, u32), seed: u32) -> f32 {
match dimension { match dimension {
d if d < sobol::MAX_DIMENSION as u32 => { d if d < sobol::MAX_DIMENSION as u32 => {
// Sobol sampling. // Sobol sampling.
// We skip the first 4 samples, because that mitigates some poor sobol::sample(d, i, seed)
// sampling at low sample counts like 16.
sobol::sample(d, i + 4, seed)
// halton::sample(d, i + seed)
} }
d => { d => {
// Random sampling. // Random sampling.

4
sub_crates/sobol/src/lib.rs
View File

@ -15,8 +15,12 @@ include!(concat!(env!("OUT_DIR"), "/vectors.inc"));
/// parameter exceeds 2^16-1, the sample set will start repeating. /// parameter exceeds 2^16-1, the sample set will start repeating.
#[inline] #[inline]
pub fn sample(dimension: u32, index: u32, seed: u32) -> f32 { pub fn sample(dimension: u32, index: u32, seed: u32) -> f32 {
// This index shuffling approach is due to Brent Burley, and is
// what allows us to create statistically independent Sobol sequences.
let shuffled_rev_index = lk_scramble(index.reverse_bits(), hash(seed, 2)); let shuffled_rev_index = lk_scramble(index.reverse_bits(), hash(seed, 2));
let scramble = hash(dimension ^ seed, 2); let scramble = hash(dimension ^ seed, 2);
let sobol = lk_scramble(sobol_u32_rev(dimension, shuffled_rev_index), scramble).reverse_bits(); let sobol = lk_scramble(sobol_u32_rev(dimension, shuffled_rev_index), scramble).reverse_bits();
u32_to_0_1_f32(sobol) u32_to_0_1_f32(sobol)
} }