Using ‘cv2.split’ method, we can Split the multi-channel image into individual color channel images.

 

Signature

dst = cv2.split(image[, mv])

 

image: Specifies the image that we want to split into individual color channels

 

mv: It is optional parameter. It's a list of indices representing the channels to be extracted.

 

dst: It is a list of NumPy arrays.

 

Example

splits = cv.split(image)

 

Find the below working application.

 

split_image_into_color_channel_images.py

import cv2 as cv
import numpy as np

# Read the image as matrix of pixels
image = cv.imread('flowers.png')
image = cv.resize(image, (800, 800))

# Default color space is BGR in OpenCV
splits = cv.split(image)

blue_channel_image = splits[0]
green_channel_image = splits[1]
red_channel_image = splits[1]

# Let's create a blank image use it in the merging process
blank_image = np.zeros(image.shape[:2], dtype='uint8')

blue = cv.merge([blue_channel_image, blank_image, blank_image])
green = cv.merge([blank_image, green_channel_image, blank_image])
red = cv.merge([blank_image, blank_image, red_channel_image])

cv.imshow('image', image)
cv.imshow('blue', blue)
cv.imshow('red', red)
cv.imshow('green', green)

# Wait for Infinite amount of time for a keyboard key to be pressed
cv.waitKey(0)

# Close the OpenCV windows
cv.destroyAllWindows()

Output

 

Original image

 

Blue color channel image (you can observe intensity of blue color)

 

 

Green color channel image (you can observe intensity of green color)

 

 

Red color channel image (you can observe intensity of red color)

  

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