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Generate FFT for raw using Python

Submitted by PhoneMod123 on

Hello, i took series of photos with closed lens cap and want to compare sensor read noise between different cameras.

Someone suggestion using FFT so i used ChatGPT to make Python script to convert ARW to FFT and Grayscale PNG files wonder if its correct script. 

import rawpy
import imageio
import numpy as np
import cv2
import os
 
def arw_to_fft(arw_path):
    # Get file name and directory
    base_dir = os.path.dirname(arw_path)
    base_name = os.path.splitext(os.path.basename(arw_path))[0]
 
    # Step 1: Read ARW file using rawpy
    with rawpy.imread(arw_path) as raw:
        rgb = raw.postprocess()
 
    # Step 2: Convert RGB to grayscale
    gray = cv2.cvtColor(rgb, cv2.COLOR_RGB2GRAY)
 
    # Step 3: Compute 2D FFT and shift zero frequency to center
    f = np.fft.fft2(gray)
    fshift = np.fft.fftshift(f)
 
    # Step 4: Calculate magnitude spectrum
    magnitude_spectrum = 20 * np.log(np.abs(fshift) + 1)  # Avoid log(0)
 
    # Normalize both images to 8-bit (0-255) for saving
    gray_8bit = cv2.normalize(gray, None, 0, 255, cv2.NORM_MINMAX).astype(np.uint8)
    mag_8bit = cv2.normalize(magnitude_spectrum, None, 0, 255, cv2.NORM_MINMAX).astype(np.uint8)
 
    # Step 5: Save the images
    gray_output_path = os.path.join(base_dir, f"{base_name}_gray.png")
    fft_output_path = os.path.join(base_dir, f"{base_name}_fft.png")
 
    cv2.imwrite(gray_output_path, gray_8bit)
    cv2.imwrite(fft_output_path, mag_8bit)
 
    print(f"Saved grayscale image: {gray_output_path}")
    print(f"Saved FFT spectrum image: {fft_output_path}")
 
 
 
arw_to_fft('C:\image.arw')

Is there some GUI or guide on how to convert RAW to FFT so i can compare it with results from this script?

My final goal just get read noise from the sensor when i simply drop files in image processor it de-mosaicing and adds colors as well which i don't want.

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