Improve visualizations: adaptive scales, revert z-score to std normalization

- MSRM/TPI/roughness/anomalies: revert z-score (x-mean)/std to std normalization x/std
  to preserve contrast and visibility of linear features (paths, ditches, trenches)
- MSRM: adaptive scales based on resolution, archaeological weight combination
- TPI: extend from 2 to 4 scales (3m/15m/50m/200m) with weighted combination
- Hillshade: 8 directions instead of 4, altitude 35° instead of 30°
- LRM: adaptive sigma based on resolution
- Openness: doubled radius (100m instead of 50m)
- Roughness: multi-scale (3m fine + 15m broad) instead of single 5x5 window
- Anomalies: uses MSRM multi-scale relief instead of single LRM 15m
- Wavelet: 8 adaptive scales, std normalization, archaeological weights
- Remove svf (Sky-View Factor) and local_dominance visualizations
- Add AVIF format support (default), quality 98
- Add multi-resolution support (-r 0.5,0.2)
- Improve Ctrl+C handling for immediate process termination
- Update rendering.py descriptions for all modified visualizations

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

lidar_pipeline/dtm.py

@@ -483,7 +483,7 @@ def create_dtm_fast(las_file, basename, dtm_dir, resolution, force=False, output
             logger.info(f"    {remaining:,} pixels restent sans données (grands écarts)")
 
         # Save as GeoTIFF
-        output_tif = dtm_dir / f"{basename}_dtm.tif"
+        output_tif = dtm_dir / f"{basename}_dtm{output_suffix}.tif"
         transform = from_bounds(min_x, min_y, max_x, max_y, width, height)
 
         with rasterio.open(