图像加噪 - 简书

图像加噪

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介绍

在有些情况下，会因为研究需要所以用一些增加了噪声的图片

文件目录树

│  GaussianNoise.py               #高斯噪声
│  SpicedSaltNoise.py         #盐椒噪声
│  
├─images       #将所有需要处理的所有图片该文件夹内
│      test.jpg   #原图
│      
└─noise_img
    ├─Gussian_noise_img           #存放加入高斯噪声图像的文件夹
    │      Gussian_noise_test.jpg 
    │      
    └─salt-and-pepper_noise_img       #存放加入盐椒噪声图像的文件夹
            salt-and-pepper_noise_test.jpg

高斯噪声

# 增加高斯噪声
from skimage import io
import random
import numpy as np
import os
import matplotlib

def gauss_noise(image):
    img = image.astype(np.int16)  # 此步是为了避免像素点小于0，大于255的情况
    mu = 0
    sigma = 10
    for i in range(img.shape[0]):
        for j in range(img.shape[1]):
            for k in range(img.shape[2]):
                img[i, j, k] = img[i, j, k] + random.gauss(mu=mu, sigma=sigma)
    img[img > 255] = 255
    img[img < 0] = 0
    img = img.astype(np.uint8)
    return img


if __name__ == '__main__':
    # 读取images文件夹内的图片名称
    images_list = os.listdir('images/')
    for i in range(0, len(images_list), 1):
        img = io.imread(r"images/"+images_list[i])
        # noise_img = salt_and_pepper_noise(img)
        gauss_img = gauss_noise(img)
        # io.imshow(gauss_img)
        # io.show()
        if (os.path.exists('noise_img\\Gussian_noise_img') == False):
            os.mkdir("noise_img\\Gussian_noise_img")    #此步骤用于判断有无存放噪声图片的文件夹，没有则创建

        matplotlib.image.imsave("noise_img/Gussian_noise_img/"+"Gussian_noise_" + images_list[i], gauss_img) #numpy数组转换为图片保存

盐椒噪声

#增加椒盐噪声
from skimage import io
import random
import numpy as np
import os
import matplotlib

def salt_and_pepper_noise(img, proportion=0.10):   #此处数值设置椒盐噪声强度
    noise_img = img
    height, width = noise_img.shape[0], noise_img.shape[1]
    num = int(height * width * proportion)  # 多少个像素点添加椒盐噪声
    for i in range(num):
        w = random.randint(0, width - 1)
        h = random.randint(0, height - 1)
        if random.randint(0, 1) == 0:
            noise_img[h, w] = 0
        else:
            noise_img[h, w] = 255
    return noise_img


if __name__ == '__main__':

    images_list = os.listdir('images/')
    for i in range(0, len(images_list), 1):
        img = io.imread(r"images/"+images_list[i])
        noise_img = salt_and_pepper_noise(img)
        # io.imshow(noise_img)
        # io.show()
        if (os.path.exists('noise_img\\salt-and-pepper_noise_img') == False):
            os.mkdir("noise_img\\salt-and-pepper_noise_img")    #此步骤用于判断有无存放噪声图片的文件夹，没有则创建

        matplotlib.image.imsave("noise_img/salt-and-pepper_noise_img/"+"salt-and-pepper_noise_" + images_list[i], noise_img) #numpy数组转换为图片保存