I have been trying different parameters, and methods of Fourier transform to remove wave pattern artifacts from my (.tiff) image but was unsuccessful in most instances. I read this wonderful stackoverflow answer but it didn’t help me much. at this point I am confused. How to remove repititve pattern from an image using FFT

image, i am working with Mouse Brain Scan montage

I have tried the code, posted on the aforementioned stackoverflow question including this below code, I had written earlier:

def fourier_masker(image):
    dark_image_fourier = np.fft.fftshift(np.fft.fft2(image))
    
    mask_vertical = np.ones_like(dark_image_fourier)
    center_col = mask_vertical.shape[1] // 2
    mask_vertical[:, center_col-1:center_col+2] = 0
    
    mask_horizontal = np.ones_like(dark_image_fourier)
    center_row = mask_horizontal.shape[0] // 2
    mask_horizontal[center_row-1:center_row+2, :] = 0
    
    dark_image_fourier *= mask_vertical * mask_horizontal
    
    masked_log_spectrum = np.log(abs(dark_image_fourier) + 1)  # Add 1 to avoid log(0)
    masked_log_spectrum -= np.min(masked_log_spectrum)  # Normalize the spectrum
    
    plt.figure(figsize=(10, 5))
    plt.subplot(1, 2, 1)
    plt.imshow(masked_log_spectrum, cmap='gray')
    plt.title('Masked Fourier')
    plt.axis('off')
    
    restored_image = np.abs(np.fft.ifft2(np.fft.ifftshift(dark_image_fourier)))
    restored_image -= np.min(restored_image)
    restored_image /= np.max(restored_image)
    
    plt.subplot(1, 2, 2)
    plt.imshow(restored_image, cmap='gray')
    plt.title('Transformed Greyscale Image')
    plt.axis('off')
    
    plt.show()

I used a grayscale image and its a tiff image.