CODEWITHSUNDEEP
pythonopencvraspberry-pirgb
Andres Mitre
Andres Mitre

Reputation: 701

subtracting RGB values from an Image in Python

I'm working in a project where I need to subtract the RGB values from an Image. In example I want to subtract the BLUE channel from RED, so RED gets the difference value of the subtraction.

I have the next properties of the image:
Dimension:1456x2592, bpp:3

The image I'm using gives me the following arrays:

 [[[ 63  58  60]
     [ 63  58  60]
     [ 64  59  61]
      ...,  
     [155 155 161]  
     [155 155 161] 
     [155 155 161]]

     [[ 58  53  55]
      [ 60  55  57]
      [ 62  57  59]
       ...,  
      [157 157 163]
      [157 157 163]
      [158 158 164]]

I know those are the values(RGB) from the image, so now I move on to do the code (I based on this code) 

import cv2
import numpy as np
from PIL import Image 

# read image into matrix.
m =  cv2.imread("ITESO.jpeg")


# get image properties.
h,w,bpp = np.shape(m)

# iterate over the entire image.
# BLUE = 0, GREEN = 1, RED = 2.    

for py in range(0,h):
    for px in range(0,w):
        #m[py][px][2] = 2   
        n = m[py][px][2]                //n takes the value of RED
        Y = [n, 0, 0]                   //I create an array with [RED, 0, 0]
        m, Y = np.array(m), np.array(Y) 
        m =  np.absolute(m - Y)       //Get the matriz with the substraction 


y = 1
x = 1
print (m)
print (m[x][y]) 

#display image
#cv2.imshow('matrix', m)
#cv2.waitKey(0)
cv2.imwrite('new.jpeg',m)
img = Image.open('new.jpeg')
img.show()

img = Image.open('new.jpeg').convert('L')
img.save('new_gray_scale.jpg')
img.show()

When I print the J matrix it gives the following arrays:

B,G,R

Blue = BLUE - RED

[[[  3  58  60]
  [  3  58  60] 
  [  4  59  61]
  ...,  
 [ 95 155 161]
 [ 95 155 161] 
 [ 95 155 161]]

[[  2  53  55] 
 [  0  55  57]
 [  2  57  59]
 ...,  
 [ 97 157 163] 
 [ 97 157 163] 
 [ 98 158 164]]

But I'm not able to open the new image and if I set one RGB channel to one value it shows me the image. I use the next lines for that:

import cv2
import numpy as np

# read image into matrix.
m =  cv2.imread("python.png")

# get image properties.
h,w,bpp = np.shape(m)

# iterate over the entire image.
for py in range(0,h):
    for px in range(0,w):
        m[py][px][0] = 0 //setting channel Blue to values of 0

# display image
cv2.imshow('matrix', m)
cv2.waitKey(0)

How can I subtract the RGB channels from each other?

PS: In MatLab it works like a charm, but I'm not able to do it in python.

Upvotes: 5

Views: 7073

Answers (2)

Andres Mitre
Andres Mitre

Reputation: 701

Code manipulating RGB negative values to zero...

m =  cv2.imread("img.jpg")

# get image properties.
h,w,bpp = np.shape(m)

    # iterate over the entire image.
    # BLUE = 0, GREEN = 1, RED = 2.

    for py in range(0,h):
        for px in range(0,w):
            n = m[py][px][1]
            Y = [0, 0, n]
            m, Y = np.array(m), np.array(Y)
            a = (m - Y)
            if (a[py][px][0] <=0): #if Blue is negative or equal 0
                a[py][px][0] = 0   #Blue set to 0 
    cv2.imwrite('img_R-G.jpg',a)
    img = Image.open('img_R-G.jpg').convert('L')
    img.save('img_R-G_GS.jpg')

Upvotes: 0

Berriel
Berriel

Reputation: 13611

Pay attention that this operation is changing the dtype of the matrix (image) from uint8 to int32, and this can cause other problems. A better way (and more efficient) to do this, IMO, is this:

import cv2
import numpy as np

img =  cv2.imread('image.png').astype(np.float)  # BGR, float
img[:, :, 2] = np.absolute(img[:, :, 2] - img[:, :, 0])  # R = |R - B|
img = img.astype(np.uint8)  # convert back to uint8
cv2.imwrite('new-image.png', img)  # save the image
cv2.imshow('img', img)
cv2.waitKey()

Upvotes: 6

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