diff --git a/pdf_cleaner.py b/pdf_cleaner.py
index d115c2d..95d9d1a 100755
--- a/pdf_cleaner.py
+++ b/pdf_cleaner.py
@@ -96,12 +96,18 @@ def trim_whitespace(image_path: str) -> bool:
         # Open image with PIL
         image = Image.open(image_path)
         
-        # Convert to grayscale if not already
-        if image.mode != 'L':
-            image = image.convert('L')
+        # Create flattened version with white background for finding bounds
+        flattened = Image.new('RGB', image.size, 'white')
+        if image.mode == 'RGBA':
+            flattened.paste(image, mask=image.split()[3])
+        else:
+            flattened.paste(image)
+            
+        # Convert to grayscale for finding bounds
+        flattened = flattened.convert('L')
         
         # Get the bounding box of non-white pixels
-        bbox = image.getbbox()
+        bbox = flattened.getbbox()
         if not bbox:
             print(f"Warning: No content found in {image_path}")
             return False
@@ -115,11 +121,11 @@ def trim_whitespace(image_path: str) -> bool:
         x2 = min(width, x2 + padding)
         y2 = min(height, y2 + padding)
         
-        # Crop the image
-        image = image.crop((x1, y1, x2, y2))
+        # Crop the original image (preserving transparency)
+        cropped = image.crop((x1, y1, x2, y2))
         
-        # Save the image
-        image.save(image_path, "PNG", optimize=False)
+        # Save the cropped image
+        cropped.save(image_path, "PNG", optimize=False)
         return True
         
     except Exception as e:
@@ -203,25 +209,44 @@ def deskew():
 def convert_to_monochrome(image_path: str) -> bool:
     """Convert image to 1-bit monochrome.
     
+    Handles RGBA images by converting transparent pixels to white before thresholding.
+    
     Returns:
         bool: True if successful, False otherwise
     """
     try:
-        # Read the image
-        img = cv2.imread(image_path)
-        if img is None:
-            print(f"Warning: Could not read image {image_path}")
-            return False
+        # Open image with PIL
+        image = Image.open(image_path)
+        
+        # Convert to RGBA if not already
+        if image.mode != 'RGBA':
+            image = image.convert('RGBA')
+        
+        # Get the image data as a list of pixels
+        data = image.getdata()
+        
+        # Create new image data, replacing transparent pixels with white
+        new_data = []
+        for item in data:
+            # If pixel is transparent (alpha < 128), make it white
+            if item[3] < 128:
+                new_data.append((255, 255, 255, 255))
+            else:
+                new_data.append(item)
+        
+        # Create new image with modified data
+        image.putdata(new_data)
         
         # Convert to grayscale
-        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+        image = image.convert('L')
         
-        # Apply threshold
-        _, mono = cv2.threshold(gray, settings.MONOCHROME_THRESHOLD, 255, cv2.THRESH_BINARY)
+        # Convert to 1-bit using threshold
+        image = image.point(lambda x: 255 if x > settings.MONOCHROME_THRESHOLD else 0, '1')
         
         # Save the monochrome image
-        cv2.imwrite(image_path, mono)
+        image.save(image_path, "PNG", optimize=False)
         return True
+        
     except Exception as e:
         print(f"Error converting to monochrome {image_path}: {str(e)}")
         return False