How to fast change image brightness with python + OpenCV?

Question

I have a sequence of images. I need to average brightness of these images.

First example (very slow):

img = cv2.imread(\'test.jpg\')         


        

Answer 1

I know this question is a bit old, but I thought I might post the complete solution that worked for me (takes care of the overflow situation by saturating at 255):

def increase_brightness(img, value=30):
    hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
    h, s, v = cv2.split(hsv)

    lim = 255 - value
    v[v > lim] = 255
    v[v <= lim] += value

    final_hsv = cv2.merge((h, s, v))
    img = cv2.cvtColor(final_hsv, cv2.COLOR_HSV2BGR)
    return img

This can be used as follows:

frame = increase_brightness(frame, value=20)

Answer 2

The other answers suggest doing the saturation "by hand" using all kinds of numpy magic, but you can also use cv2.add() and let OpenCV handle that for you:

import cv2
import numpy as np

image = cv2.read('image.png')
hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
value = 42 #whatever value you want to add
cv2.add(hsv[:,:,2], value, hsv[:,:,2])
image = cv2.cvtColor(hsv, cv2.COLOR_HSV2BGR)
cv2.imwrite('out.png', image)

Answer 3

Slice to select just the third channel and then modify those elements -

hsv[:,:,2] += value

Answer 4

This was my solution to both increase and decrease brightness. Was having some error issues with a couple of the other answers. Function takes in a positive or negative value and alters brightness.

example in code

img = cv2.imread(path_to_image)
img = change_brightness(img, value=30) #increases
img = change_brightness(img, value=-30) #decreases

function being called

def change_brightness(img, value=30):
    hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
    h, s, v = cv2.split(hsv)
    v = cv2.add(v,value)
    v[v > 255] = 255
    v[v < 0] = 0
    final_hsv = cv2.merge((h, s, v))
    img = cv2.cvtColor(final_hsv, cv2.COLOR_HSV2BGR)
return img

Answer 5

Iterating over the whole image to make changes is not a very scalable option in opencv, Opencv provides a lot of methods and functions to perform the arithmetic operations on the given image.

You may simply split the converted HSV image in the individual channels and then process the V channel accordingly as:

img = cv2.imread('test.jpg') #load rgb image
hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV) #convert it to hsv

h, s, v = cv2.split(hsv)
v += 255
final_hsv = cv2.merge((h, s, v))

img = cv2.cvtColor(final_hsv, cv2.COLOR_HSV2BGR)
cv2.imwrite("image_processed.jpg", img)

Answer 6

def change_brightness(img, alpha, beta):
   return cv2.addWeighted(img, alpha, np.zeros(img.shape, img.dtype),0, beta)

Here alpha & beta are input parameters. Each pixel of the input image will change according to this formula.

 alpha(pixel_value) + beta.

Lower value of alpha like 2 or 3 is good