diff --git a/nodes/greenscreen.py b/nodes/greenscreen.py
index 4392b43..c488f0b 100644
--- a/nodes/greenscreen.py
+++ b/nodes/greenscreen.py
@@ -10,6 +10,14 @@ from comfy.utils import ProgressBar
 logger = logging.getLogger("CorridorKey")
 
 
+def _linear_to_srgb(x: np.ndarray) -> np.ndarray:
+    return np.where(
+        x <= 0.0031308,
+        x * 12.92,
+        1.055 * np.power(np.maximum(x, 0.0031308), 1.0 / 2.4) - 0.055,
+    )
+
+
 class CorridorKeyGreenscreen:
     @classmethod
     def INPUT_TYPES(cls):
@@ -49,7 +57,7 @@ class CorridorKeyGreenscreen:
     CATEGORY = "CorridorKey"
     DESCRIPTION = (
         "Neural network greenscreen keying. Produces a clean alpha matte, "
-        "despilled straight foreground, premultiplied linear RGBA, and a "
+        "despilled sRGB foreground, straight sRGB RGBA, and a "
         "checkerboard composite preview."
     )
 
@@ -114,11 +122,21 @@ class CorridorKeyGreenscreen:
                 alpha_out = alpha_out[:, :, 0]
             alphas.append(torch.from_numpy(alpha_out))
 
-            # fg: [H,W,3] sRGB straight float -> IMAGE [H,W,C]
-            fgs.append(torch.from_numpy(result["fg"]))
+            # Derive clean despilled foreground from processed RGBA:
+            # processed is [H,W,4] linear premultiplied — un-premultiply, then
+            # convert to sRGB to get a foreground that looks like comp_preview
+            # but without any background baked in.
+            processed_raw = result["processed"]  # [H,W,4] linear premul
+            proc_alpha = processed_raw[:, :, 3:4]
+            proc_rgb = processed_raw[:, :, :3]
+            safe_alpha = np.maximum(proc_alpha, 1e-7)
+            straight_lin = proc_rgb / safe_alpha
+            straight_srgb = _linear_to_srgb(np.clip(straight_lin, 0.0, 1.0))
+            fgs.append(torch.from_numpy(np.clip(straight_srgb, 0.0, 1.0).astype(np.float32)))
 
-            # processed: [H,W,4] linear premultiplied RGBA -> IMAGE [H,W,C]
-            processed_list.append(torch.from_numpy(result["processed"]))
+            # processed RGBA: convert to sRGB straight for usable output
+            proc_srgb = np.concatenate([straight_srgb, proc_alpha], axis=2)
+            processed_list.append(torch.from_numpy(np.clip(proc_srgb, 0.0, 1.0).astype(np.float32)))
 
             # comp: [H,W,3] sRGB checkerboard composite -> IMAGE [H,W,C]
             comps.append(torch.from_numpy(result["comp"]))