Add a "salt and pepper" noise to an image with Python (original) (raw)

Last Updated : 23 Jul, 2025

In this article, we are going to see how to add a "salt and pepper" noise to an image with Python.

Noise: Noise means random disturbance in a signal in a computer version. In our case, the signal is an image. Random disturbance in the brightness and color of an image is called Image noise.

Salt-and-pepper: It is found only in grayscale images (black and white image). As the name suggests salt (white) in pepper (black)--white spots in the dark regions or pepper (black) in salt (white)--black spots in the white regions. In other words, an image having salt-and-pepper noise will have a few dark pixels in bright regions and a few bright pixels in dark regions. Salt-and-pepper noise is also called impulse noise. It can be caused by several reasons like dead pixels, analog-to-digital conversion error, bit transmission error, etc.

Let's see how to add salt-and-pepper noise in an image -

• Salt-and-pepper noise can only be added in a grayscale image. So, convert an image to grayscale after reading it
• Randomly pick the number of pixels to which noise is added (number_of_pixels)
• Randomly pick some pixels in the image to which noise will be added. It can be done by randomly picking x and y coordinate
• Note the random values generated must be within the range of the image dimensions. The x and y coordinates must be within the range of the image size
• Random numbers can be generated using random number generator functions like random.randint used in the code
• Color some randomly picked pixels as black setting their value to 0
• Color some randomly picked pixels as white setting their value to 255
• Save the value of the image

Below is the implementation:

Python `

import random import cv2

def add_noise(img):

# Getting the dimensions of the image
row , col = img.shape

# Randomly pick some pixels in the
# image for coloring them white
# Pick a random number between 300 and 10000
number_of_pixels = random.randint(300, 10000)
for i in range(number_of_pixels):
  
    # Pick a random y coordinate
    y_coord=random.randint(0, row - 1)
    
    # Pick a random x coordinate
    x_coord=random.randint(0, col - 1)
    
    # Color that pixel to white
    img[y_coord][x_coord] = 255
    
# Randomly pick some pixels in
# the image for coloring them black
# Pick a random number between 300 and 10000
number_of_pixels = random.randint(300 , 10000)
for i in range(number_of_pixels):
  
    # Pick a random y coordinate
    y_coord=random.randint(0, row - 1)
    
    # Pick a random x coordinate
    x_coord=random.randint(0, col - 1)
    
    # Color that pixel to black
    img[y_coord][x_coord] = 0
    
return img

salt-and-pepper noise can

be applied only to grayscale images

Reading the color image in grayscale image

img = cv2.imread('lena.jpg', cv2.IMREAD_GRAYSCALE)

#Storing the image cv2.imwrite('salt-and-pepper-lena.jpg', add_noise(img))

`

Output:

Input image: "lena.jpg"

Output image: "Salt-and-pepper-lena.jpg"