feat: switch from enblend to verdandi for blending

verdandi eliminates overexposure at seam transitions, especially on
Mastcam-Z panoramas. Also faster than enblend.

Benchmark results:
- MCZ sol 1817: 0 bright cols (vs 142 with enblend)
- MCZ sol 1775: 1 bright col (vs 1105 with enblend)
- Faster: 1s vs 2.3s (sol 1817), 66s vs 174s (sol 1775)

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

README.md

@@ -44,7 +44,7 @@ docker compose run panorama --sol 1813 --camera NAVCAM_LEFT
 5. **cpclean** — Remove outlier control points
 6. **Swap to originals** — Replace CLAHE images with originals in PTO
 7. **autooptimiser** — Geometry-only optimization (NO photometric -m flag)
-8. **nona + enblend** — Remap and blend final panorama
+8. **nona + verdandi** — Remap and blend final panorama (verdandi eliminates overexposure at seams)
 9. **Export PNG** — Convert TIFF output to PNG
 
 ## Supported Cameras

pipeline/panorama_pipeline.py

@@ -279,7 +279,7 @@ def build_pto(pto_path, img_paths, azs, els, img_w, img_h, fov, ref_idx=None):
 
 def run_pipeline(work_dir, clahe_images, original_images, azs, els,
                  img_w, img_h, fov, output_name):
-    """Full pipeline: cpfind(CLAHE) -> swap(originals) -> optimize(geo) -> nona -> enblend."""
+    """Full pipeline: cpfind(CLAHE) -> swap(originals) -> optimize(geo) -> nona -> verdandi."""
 
     timings = {}
 
@@ -351,13 +351,13 @@ def run_pipeline(work_dir, clahe_images, original_images, azs, els,
         print("  ERROR: nona produced no output")
         return None, timings
 
-    # enblend
-    print("  enblend...", flush=True)
+    # verdandi (better transitions than enblend, no overexposure at seams)
+    print("  verdandi...", flush=True)
     out_tif = os.path.join(work_dir, f"{output_name}.tif")
     tif_list = " ".join([f'"{t}"' for t in tifs])
     t0 = time.time()
-    run_hugin("enblend", f'--pre-assemble -o "{out_tif}" {tif_list}', cwd=work_dir)
-    timings["enblend"] = time.time() - t0
+    run_hugin("verdandi", f'-o "{out_tif}" {tif_list}', cwd=work_dir)
+    timings["verdandi"] = time.time() - t0
 
     # Convert to PNG
     out_png = os.path.join(work_dir, f"{output_name}.png")