# _*_ coding:utf-8 _*_
# @Time : 17:23
# @Author :baizhou
import cv2
import matplotlib.pyplot as plt
import os
import numpy as np
from skimage import exposure
def SaltAndPepper(src, percetage):
SP_NoiseImg = src.copy()
SP_NoiseNum = int(percetage * src.shape[0] * src.shape[1])
for i in range(SP_NoiseNum):
randR = np.random.randint(0, src.shape[0] - 1)
randG = np.random.randint(0, src.shape[1] - 1)
randB = np.random.randint(0, 3)
if np.random.randint(0, 1) == 0:
SP_NoiseImg[randR, randG, randB] = 0
else:
SP_NoiseImg[randR, randG, randB] = 255
return SP_NoiseImg
def addGaussianNoise(image, percetage):
G_Noiseimg = image.copy()
w = image.shape[1]
h = image.shape[0]
G_NoiseNum = int(percetage * image.shape[0] * image.shape[1])
for i in range(G_NoiseNum):
temp_x =