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/gpu.py

@@ -110,6 +110,16 @@ def xp_minimum_filter(arr, footprint=None, size=None):
     return ndimage.minimum_filter(arr, footprint=footprint, size=size)
 
 
+def xp_maximum_filter(arr, footprint=None, size=None):
+    """Maximum filter — uses GPU if array is on GPU, CPU otherwise."""
+    if _cp is not None and isinstance(arr, _cp.ndarray):
+        try:
+            return _cp_ndimage.maximum_filter(arr, footprint=footprint, size=size)
+        except Exception:
+            arr = to_cpu(arr)
+    return ndimage.maximum_filter(arr, footprint=footprint, size=size)
+
+
 def gpu_cleanup():
     """Free GPU memory. Call between visualizations to prevent OOM."""
     if _cp is not None: