Convert image to grayscale with custom luminosity formula

Question

I have images containing gray gradations and one another color. I'm trying to convert image to grayscale with opencv, also i want the colored pixels in the source image to become rather light in the output grayscale image, independently to the color itself.

The common luminosity formula is smth like 0.299R+0.587G+0.114B, according to opencv docs, so it gives very different luminosity to different colors.

I consider the solution is to set some custom weights in the luminosity formula. Is it possible in opencv? Or maybe there is a better way to perform such selective desaturation?

I use python, but it doesnt matter

Answer 1

This is the perfect case for the transform() function. You can treat grayscale conversion as applying a 1x3 matrix transformation to each pixel of the input image. The elements in this matrix are the coefficients for the blue, green, and red components, respectively since OpenCV images are BGR by default.

im = cv2.imread(image_path)
coefficients = [1,0,0] # Gives blue channel all the weight
# for standard gray conversion, coefficients = [0.114, 0.587, 0.299]
m = np.array(coefficients).reshape((1,3))
blue = cv2.transform(im, m)

Answer 2

So you have custom formula,

Load source,

Mat src=imread(fileName,1);

Create gray image,

Mat gray(src.size(),CV_8UC1,Scalar(0));

Now in a loop, access BGR pixel of source like,

Vec3b bgrPixel=src.at<cv::Vec3b>(y,x); //gives you the BGR vector of type cv::Vec3band will be in row, column order

bgrPixel[0]= Blue//
bgrPixel[1]= Green//
bgrPixel[2]= Red//

Calculate new gray pixel value using your custom equation.

Finally set the pixel value on gray image,

 gray.at<uchar>(y,x) = custom intensity value // will be in row, column order