32 lines
1.5 KiB
HLSL
32 lines
1.5 KiB
HLSL
#ifndef _SAMPLING_SOBOLBLUENOISESAMPLING_HLSL_
|
|
#define _SAMPLING_SOBOLBLUENOISESAMPLING_HLSL_
|
|
|
|
#include "SamplingResources.hlsl"
|
|
|
|
// This is an implementation of the method from the paper
|
|
// "A Low-Discrepancy Sampler that Distributes Monte Carlo Errors as a Blue Noise in Screen Space" by Heitz et al.
|
|
float GetBNDSequenceSample(uint2 pixelCoord, uint sampleIndex, uint sampleDimension)
|
|
{
|
|
// wrap arguments
|
|
pixelCoord = pixelCoord & 127;
|
|
sampleIndex = sampleIndex & 255;
|
|
sampleDimension = sampleDimension & 255;
|
|
|
|
// xor index based on optimized ranking
|
|
uint rankingIndex = (pixelCoord.x + pixelCoord.y * 128) * 8 + (sampleDimension & 7);
|
|
uint rankedSampleIndex = sampleIndex ^ clamp((uint)(_SobolRankingTile[uint2(rankingIndex & 127, rankingIndex / 128)] * 256.0), 0, 255);
|
|
|
|
// fetch value in sequence
|
|
uint value = clamp((uint)(_SobolOwenScrambledSequence[uint2(sampleDimension, rankedSampleIndex.x)] * 256.0), 0, 255);
|
|
|
|
// If the dimension is optimized, xor sequence value based on optimized scrambling
|
|
uint scramblingIndex = (pixelCoord.x + pixelCoord.y * 128) * 8 + (sampleDimension & 7);
|
|
float scramblingValue = min(_SobolScramblingTile[uint2(scramblingIndex & 127, scramblingIndex / 128)], 0.999);
|
|
value = value ^ uint(scramblingValue * 256.0);
|
|
|
|
// Convert to float (to avoid the same 1/256th quantization everywhere, we jitter by the pixel scramblingValue)
|
|
return (max(0.001, scramblingValue) + value) / 256.0;
|
|
}
|
|
|
|
#endif // _SAMPLING_SOBOLBLUENOISESAMPLING_HLSL_
|