How do I increase the contrast of an image in Python OpenCV

tsaebeht picture tsaebeht · Sep 3, 2016 · Viewed 105.1k times · Source

I am new to Python OpenCV. I have read some documents and answers here but I am unable to figure out what the following code means:

if (self.array_alpha is None):
    self.array_alpha = np.array([1.25])
    self.array_beta = np.array([-100.0])

# add a beta value to every pixel 
cv2.add(new_img, self.array_beta, new_img)                    

# multiply every pixel value by alpha
cv2.multiply(new_img, self.array_alpha, new_img)  

I have come to know that Basically, every pixel can be transformed as X = aY + b where a and b are scalars.. Basically, I have understood this. However, I did not understand the code and how to increase contrast with this.

Till now, I have managed to simply read the image using img = cv2.imread('image.jpg',0)

Thanks for your help

Answer

Jeru Luke picture Jeru Luke · Dec 10, 2016

I would like to suggest a method using the LAB color channel. Wikipedia has enough information regarding what the LAB color channel is about.

I have done the following using OpenCV 3.0.0 and python:

import cv2

#-----Reading the image-----------------------------------------------------
img = cv2.imread('Dog.jpg', 1)
cv2.imshow("img",img) 

#-----Converting image to LAB Color model----------------------------------- 
lab= cv2.cvtColor(img, cv2.COLOR_BGR2LAB)
cv2.imshow("lab",lab)

#-----Splitting the LAB image to different channels-------------------------
l, a, b = cv2.split(lab)
cv2.imshow('l_channel', l)
cv2.imshow('a_channel', a)
cv2.imshow('b_channel', b)

#-----Applying CLAHE to L-channel-------------------------------------------
clahe = cv2.createCLAHE(clipLimit=3.0, tileGridSize=(8,8))
cl = clahe.apply(l)
cv2.imshow('CLAHE output', cl)

#-----Merge the CLAHE enhanced L-channel with the a and b channel-----------
limg = cv2.merge((cl,a,b))
cv2.imshow('limg', limg)

#-----Converting image from LAB Color model to RGB model--------------------
final = cv2.cvtColor(limg, cv2.COLOR_LAB2BGR)
cv2.imshow('final', final)

#_____END_____#

You can run the code as it is. To know what CLAHE (Contrast Limited Adaptive Histogram Equalization)is about, you can again check Wikipedia.