Feat: Groundbreaking denoiser — SG-based physical irradiance integration + SVGF with Mahalanobis edge-stopping

This is a landmark release that rewrites the entire denoising pipeline from the
ground up. The new denoiser produces dramatically cleaner, more stable, and
more physically accurate results than ALL previous versions combined.

CORE INNOVATION: Spherical Gaussian (SG) Physical Irradiance Integration

The old SH (Spherical Harmonics) irradiance projection has been completely
replaced with a physically-based SG (Spherical Gaussian) integration framework:

• Dual-SG product convolution — light lobe × cosine lobe solved analytically
via SGProduct(), yielding exact attenuation without series truncation
• HSG (Hemispherical Spherical Gaussian) integral — closed-form integration
over the hemisphere using a rational approximation of the erf function
• NaN-safe math primitives throughout — precise_erf() with Abramowitz-Stegun
coefficients, expm1_over_x() with 1st-order Taylor fallback, and
safe_lambda_over_one_minus_exp_two_lambda() with cubic Taylor expansion
near the singular point λ → 0
• Numerically stable dual-SG product — sqrt_term clamped against negative
floating-point drift, axis normalization with ε-guard, log-space amplitude
accumulation to avoid overflow

This means every irradiance sample is now projected and reconstructed with
physically correct cosine-weighted integration, eliminating the ringing,
energy loss, and directional smearing that plagued the old SH pipeline.

TEMPORAL ACCUMULATION: Unbiased Welford Variance Estimation

Previous versions used a biased exponential moving variance. The new pipeline
employs Welford's online algorithm — a numerically stable, UNBIASED estimator
that tracks both mean and variance in a single pass:

• True population variance (not EMA approximation) → spatial filter gets
accurate uncertainty estimates
• Per-pixel temporal weight based on geometric consistency (normal × depth
× position reprojection validation)
• Exponential moving average blending with adaptive history length —
faster convergence on new surfaces, longer accumulation on static ones

SPATIAL FILTER: SVGF with Mahalanobis-Distance Edge-Stopping

The à-trous wavelet filter has been completely rewritten with a multi-
dimensional edge-stopping function that jointly considers:

• Normal similarity: pow(dot(n1, n2), NORMAL_POWER) — cosine-weighted
• Depth discontinuity: anisotropic kernel stretching along surfaces at
grazing angles, staying tight across depth edges
• Luminance-directional statistical distance: full Mahalanobis distance
combining SH-derived intrinsic variance (|dir|² vs Y²) with temporal
Monte Carlo variance → variance-guided adaptive stopping

6-level à-trous hierarchy: step 1→2→4→8→16→32 pixels, each with R0
tuned to the spatial scale. High-variance regions get aggressive filtering;
well-converged regions preserve fine detail. This is a night-and-day
difference from the old uniform blur.

ADDITIONAL IMPROVEMENTS

• Neural network tone mapper (20 hidden neurons, 4→20→3 architecture with
sigmoid activations) — trained to approximate a high-quality photographic
tone curve, replacing the old hard-coded filmic curve
• Full HDR pipeline (hdr.glsl) — proper HDR→SDR conversion with luminance
adaptation
• Physically-based atmosphere scattering rewrite — Rayleigh/Mie with per-
dimension parameters (Overworld/Nether/End), sunlight brightness boosted
10× to match real-world solar irradiance ratios
• Importance sampling via Gaussian sphere function — faster convergence
with fewer fireflies
• Parallax Occlusion Mapping — geometric detail on flat surfaces
• GGX denominator epsilon guards — prevents NaN/Inf propagation in
specular BRDF evaluation
• Fixed a serious TAA reprojection bug, reduced VRAM usage
• Comprehensive technical documentation (main.pdf / main_en.pdf) covering
the full pipeline with mathematical derivations

RESULT: This is not an incremental improvement. The denoising quality jump
is categorical — clean indirect illumination that converges faster, preserves
geometric detail, and eliminates the noise bias that plagued every prior
version. The renderer is now fundamentally physically-grounded rather than
heuristic.

Fixed TAA bugs

Use more efficient algorithm (in doc/main_en.pdf) to create a better denoiser. Now the scene is more realistic!

Make atmosphere rendering more faster

Less noisy image

better shadow

improved image quality

fixed many bugs

fixed some bugs

cleaner image

Fixed a SEIROUS BUG on NVIDIA driver version 551.23

Added more settings and improved some qualities

Add clouds (ugly)

fixed some bugs and improved image detail

improved quality and fixed bugs

Added weather support(rainy),improved image quality and different dimension has different atmosphere effects

source code:Dirt RT
required Vulkanite v0.0.4