Add RRIM, Multi-Hillshade RGB, and Local Dominance visualizations

Three new visualizations complementing existing SVF/openness/LRM/MSRM:

- RRIM (Red Relief Image Map): RGB composite combining positive openness
  (R), inverted slope (G), negative openness (B). Uses ray-tracing
  to compute both openness values in a single pass.

- Multi-Hillshade RGB: 3 azimuths (315°, 135°, 45°) mapped to R/G/B
  channels with slope blending. Color reveals structure orientation.

- Local Dominance: (dem - local_min) / (local_max - local_min) using
  min/max filters. Measures local height position — complements openness.

Also adds:
- _compute_openness_both() helper for shared ray-tracing (used by RRIM)
- xp_maximum_filter() in gpu.py (GPU/CPU abstraction)
- Entries in COLORMAPS, RGB_LEGENDS, VIZ_STEPS, and is_rgb detection
- All NaN handling follows existing patterns (nan_mask restoration)

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

lidar_pipeline/pipeline.py

@@ -61,7 +61,7 @@ from .visualizations import (
     generate_lrm, generate_svf, generate_openness,
     generate_mslrm, generate_tpi, generate_sailore,
     generate_roughness, generate_anomalies, generate_wavelet,
-    generate_flow,
+    generate_flow, generate_rrim, generate_multi_hillshade, generate_local_dominance,
 )
 from .gpu import gpu_cleanup
 from .ign import generate_ign_overlay
@@ -87,6 +87,9 @@ VIZ_STEPS = [
     ('anomalies',  generate_anomalies),
     ('wavelet',    generate_wavelet),
     ('flow',       generate_flow),
+    ('rrim',       lambda d, b, v, r: generate_rrim(d, b, v, r)),
+    ('multi_hillshade', lambda d, b, v, r: generate_multi_hillshade(d, b, v, r)),
+    ('local_dominance', generate_local_dominance),
     ('ortho',      lambda d, b, v, r: generate_ign_overlay(
                     d, b, v, r,
                     layer='ORTHOIMAGERY.ORTHOPHOTOS',