utils.py

import cv2
import numpy as np
from skimage.metrics import structural_similarity as ssim
import math

def calculate_psnr(original, enhanced):
    mse = np.mean((original - enhanced) ** 2)
    if mse == 0:
        return 100
    max_pixel = 255.0
    return 20 * math.log10(max_pixel / math.sqrt(mse))

def calculate_ssim(original, enhanced):
    grayA = cv2.cvtColor(original, cv2.COLOR_BGR2GRAY)
    grayB = cv2.cvtColor(enhanced, cv2.COLOR_BGR2GRAY)
    score, _ = ssim(grayA, grayB, full=True)
    return score

def detect_blur(image):
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    return cv2.Laplacian(gray, cv2.CV_64F).var()

def enhance_image(image, alpha=1.5, beta=30):
    enhanced = cv2.convertScaleAbs(image, alpha=alpha, beta=beta)
    denoised = cv2.GaussianBlur(enhanced, (5,5),0)
    return denoised