diff --git a/imagelib/color_transfer.py b/imagelib/color_transfer.py
index 093ed3d..a2d4326 100644
--- a/imagelib/color_transfer.py
+++ b/imagelib/color_transfer.py
@@ -77,11 +77,11 @@ def reinhard_color_transfer(source, target, clip=False, preserve_paper=False, so
     a += aMeanTar
     b += bMeanTar
 
-    # clip/scale the pixel intensities to [0, 255] if they fall
-    # outside this range
-    l = _scale_array(l, 0, 100, clip=clip)
-    a = _scale_array(a, -127, 127, clip=clip)
-    b = _scale_array(b, -127, 127, clip=clip)
+    # clip/scale the pixel intensities if they fall
+    # outside the ranges for LAB
+    l = _scale_array(l, 0, 100, clip=clip, mask=source_mask)
+    a = _scale_array(a, -127, 127, clip=clip, mask=source_mask)
+    b = _scale_array(b, -127, 127, clip=clip, mask=source_mask)
 
     # merge the channels together and convert back to the RGB color
     transfer = cv2.merge([l, a, b])
@@ -180,7 +180,7 @@ def _min_max_scale(arr, new_range=(0, 255)):
     return scaled
 
 
-def _scale_array(arr, mn, mx, clip=True):
+def _scale_array(arr, mn, mx, clip=True, mask=None):
     """
     Trim NumPy array values to be in [0, 255] range with option of
     clipping or scaling.
@@ -197,7 +197,10 @@ def _scale_array(arr, mn, mx, clip=True):
     if clip:
         scaled = np.clip(arr, mn, mx)
     else:
-        scale_range = (max([arr.min(), mn]), min([arr.max(), mx]))
+        if mask is not None:
+            scale_range = (max([np.min(mask * arr), mn]), min([np.max(mask * arr), mx]))
+        else:
+            scale_range = (max([np.min(arr), mn]), min([np.max(arr), mx]))
         scaled = _min_max_scale(arr, new_range=scale_range)
 
     return scaled
diff --git a/imagelib/test/color_transfer.py b/imagelib/test/color_transfer.py
index 5b1338f..c570452 100644
--- a/imagelib/test/color_transfer.py
+++ b/imagelib/test/color_transfer.py
@@ -15,44 +15,44 @@ class ColorTranfer(unittest.TestCase):
         src_samples = SampleLoader.load(SampleType.FACE, './test_src', None)
         dst_samples = SampleLoader.load(SampleType.FACE, './test_dst', None)
 
-        src_sample = src_samples[2]
-        src_img = src_sample.load_bgr()
-        src_mask = src_sample.load_mask()
+        for src_sample in src_samples:
+            src_img = src_sample.load_bgr()
+            src_mask = src_sample.load_mask()
 
-        # Toggle to see masks
-        show_masks = False
+            # Toggle to see masks
+            show_masks = False
 
-        grid = []
-        for ct_sample in dst_samples:
-            print(src_sample.filename, ct_sample.filename)
-            ct_img = ct_sample.load_bgr()
-            ct_mask = ct_sample.load_mask()
+            grid = []
+            for ct_sample in dst_samples:
+                print(src_sample.filename, ct_sample.filename)
+                ct_img = ct_sample.load_bgr()
+                ct_mask = ct_sample.load_mask()
 
-            lct_img = linear_color_transfer(src_img, ct_img)
-            rct_img = reinhard_color_transfer(src_img, ct_img)
-            rct_img_clip = reinhard_color_transfer(src_img, ct_img, clip=True)
-            rct_img_paper = reinhard_color_transfer(src_img, ct_img, preserve_paper=True)
-            rct_img_paper_clip = reinhard_color_transfer(src_img, ct_img, clip=True, preserve_paper=True)
+                lct_img = linear_color_transfer(src_img, ct_img)
+                rct_img = reinhard_color_transfer(src_img, ct_img)
+                rct_img_clip = reinhard_color_transfer(src_img, ct_img, clip=True)
+                rct_img_paper = reinhard_color_transfer(src_img, ct_img, preserve_paper=True)
+                rct_img_paper_clip = reinhard_color_transfer(src_img, ct_img, clip=True, preserve_paper=True)
 
-            masked_rct_img = reinhard_color_transfer(src_img, ct_img, source_mask=src_mask, target_mask=ct_mask)
-            masked_rct_img_clip = reinhard_color_transfer(src_img, ct_img, clip=True, source_mask=src_mask, target_mask=ct_mask)
-            masked_rct_img_paper = reinhard_color_transfer(src_img, ct_img, preserve_paper=True, source_mask=src_mask, target_mask=ct_mask)
-            masked_rct_img_paper_clip = reinhard_color_transfer(src_img, ct_img, clip=True, preserve_paper=True, source_mask=src_mask, target_mask=ct_mask)
+                masked_rct_img = reinhard_color_transfer(src_img, ct_img, source_mask=src_mask, target_mask=ct_mask)
+                masked_rct_img_clip = reinhard_color_transfer(src_img, ct_img, clip=True, source_mask=src_mask, target_mask=ct_mask)
+                masked_rct_img_paper = reinhard_color_transfer(src_img, ct_img, preserve_paper=True, source_mask=src_mask, target_mask=ct_mask)
+                masked_rct_img_paper_clip = reinhard_color_transfer(src_img, ct_img, clip=True, preserve_paper=True, source_mask=src_mask, target_mask=ct_mask)
 
-            results = [lct_img, rct_img, rct_img_clip, rct_img_paper, rct_img_paper_clip,
-                       masked_rct_img, masked_rct_img_clip, masked_rct_img_paper, masked_rct_img_paper_clip]
+                results = [lct_img, rct_img, rct_img_clip, rct_img_paper, rct_img_paper_clip,
+                           masked_rct_img, masked_rct_img_clip, masked_rct_img_paper, masked_rct_img_paper_clip]
 
-            if show_masks:
-                results = [src_mask * im for im in results]
-                src_img *= src_mask
-                ct_img *= ct_mask
+                if show_masks:
+                    results = [src_mask * im for im in results]
+                    src_img *= src_mask
+                    ct_img *= ct_mask
 
-            results = np.concatenate((src_img, ct_img, *results), axis=1)
-            grid.append(results)
+                results = np.concatenate((src_img, ct_img, *results), axis=1)
+                grid.append(results)
 
-        cv2.namedWindow('test output', cv2.WINDOW_NORMAL)
-        cv2.imshow('test output', np.concatenate(grid, axis=0))
-        cv2.waitKey(0)
+            cv2.namedWindow('test output', cv2.WINDOW_NORMAL)
+            cv2.imshow('test output', np.concatenate(grid, axis=0))
+            cv2.waitKey(0)
         cv2.destroyAllWindows()