fixes to high pass and low pass,laplacian and sobel

transforms.py

@@ -24,8 +24,10 @@ def sobel_edge_detection(image):
     sobel_x = cv2.Sobel(image, cv2.CV_64F, 1, 0, ksize=3)
     sobel_y = cv2.Sobel(image, cv2.CV_64F, 0, 1, ksize=3)
     sobel_combined = np.sqrt(sobel_x**2 + sobel_y**2)
+    sobel_combined = cv2.normalize(sobel_combined, None, 0, 255, cv2.NORM_MINMAX)  # Added normalization
     return sobel_combined
 
+
 # 3. Gaussian Blur
 def gaussian_blur(image, kernel_size=5):
     blurred_img = cv2.GaussianBlur(image, (kernel_size, kernel_size), 0)
@@ -37,8 +39,10 @@ def laplacian_of_gaussian(image):
         image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
     blurred_img = cv2.GaussianBlur(image, (3, 3), 0)
     log_img = cv2.Laplacian(blurred_img, cv2.CV_64F)
+    log_img = cv2.normalize(log_img, None, 0, 255, cv2.NORM_MINMAX)  # Added normalization
     return log_img
 
+
 # 5. Median Filtering
 def median_filter(image, kernel_size=5):
     median_img = cv2.medianBlur(image, kernel_size)
@@ -66,7 +70,7 @@ def high_pass_filter(image):
     dft_shift = np.fft.fftshift(dft)
     rows, cols = image.shape
     crow, ccol = rows // 2, cols // 2
-    mask = np.ones((rows, cols), np.uint8)
+    mask = np.ones((rows, cols), np.float64)  # Changed to float64
     mask[crow-30:crow+30, ccol-30:ccol+30] = 0
     fshift = dft_shift * mask
     f_ishift = np.fft.ifftshift(fshift)
@@ -74,6 +78,7 @@ def high_pass_filter(image):
     img_back = np.abs(img_back)
     return img_back
 
+
 def low_pass_filter(image):
     if len(image.shape) == 3:  # Convert to grayscale if RGB
         image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
@@ -81,7 +86,7 @@ def low_pass_filter(image):
     dft_shift = np.fft.fftshift(dft)
     rows, cols = image.shape
     crow, ccol = rows // 2, cols // 2
-    mask = np.zeros((rows, cols), np.uint8)
+    mask = np.zeros((rows, cols), np.float64)  # Changed to float64
     mask[crow-30:crow+30, ccol-30:ccol+30] = 1
     fshift = dft_shift * mask
     f_ishift = np.fft.ifftshift(fshift)
@@ -89,6 +94,7 @@ def low_pass_filter(image):
     img_back = np.abs(img_back)
     return img_back
 
+
 def wavelet_transform(image):
     import pywt
     if len(image.shape) == 3:  # Convert to grayscale if RGB