ISP算法|图片添加高斯噪声和椒盐噪声python python|图像处理|图像细节

使用Python给图片添加高斯噪声和椒盐噪声，在研究图像降噪算法时，经常会使用到，简单的写了几行代码。

import cv2 import os import numpy as npdef Expand2Dto3D(img): img = np.expand_dims(img, axis=2) img = np.repeat(img, 3, axis=2) return imgdef AddSaltAndPepperNosie(img, pro): noise = np.random.uniform(0, 255, img[:, :, 0].shape) mask = noise < pro * 255 mask = Expand2Dto3D(mask) img = img * (1 - mask)mask = noise > 255 - pro * 255 mask = Expand2Dto3D(mask) img = 255 * mask + img * (1 - mask) return imgdef AddGaussNoise(img, sigma, mean=0): # 大概率abs(noise) < 3 * sigma noise = np.random.normal(mean, sigma, img.shape) img = img.astype(np.float) img = img + noise img = np.clip(img, 0, 255) img = img.astype(np.uint8) return imgdef AddGaussNoiseGray(img, sigma, mean=0): lab = cv2.cvtColor(img, cv2.COLOR_BGR2Lab) noise = np.random.normal(mean, sigma, lab[:, :, 0].shape) lab = lab.astype(np.float) lab[:, :, 0] = lab[:, :, 0] + noise lab[:, :, 0] = np.clip(lab[:, :, 0], 0, 255) lab = lab.astype(np.uint8) img = cv2.cvtColor(lab, cv2.COLOR_Lab2BGR) return imgif __name__ == '__main__': img = cv2.imread('test3.jpg', 1) print(img.shape) noiseImg = AddGaussNoise(img, 20, 0) cv2.imwrite('test_gauss_noise_color.jpg', noiseImg)noiseImgGray = AddGaussNoiseGray(img, 20, 0) cv2.imwrite('test_gauss_noise_gray.jpg', noiseImgGray)noiseImgSalt = AddSaltAndPepperNosie(img, 0.1) cv2.imwrite('test_salt_noise.jpg', noiseImgSalt)

效果如下：