Normalizing images in OpenCV

Question

I wrote the following code to normalize an image using NORM_L1 in OpenCV. But the output image was just black. How to solve this?

import cv2 import numpy as np import Image  img = cv2.imread('img7.jpg') gray_image = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) a = np.asarray(gray_image)   dst = np.zeros(shape=(5,2))  b=cv2.normalize(a,dst,0,255,cv2.NORM_L1)   im = Image.fromarray(b)  im.save("img50.jpg")  cv2.waitKey(0) cv2.destroyAllWindows() 

Answer 1

If you want to change the range to [0, 1], make sure the output data type is float.

image = cv2.imread("lenacolor512.tiff", cv2.IMREAD_COLOR)  # uint8 image norm_image = cv2.normalize(image, None, alpha=0, beta=1, norm_type=cv2.NORM_MINMAX, dtype=cv2.CV_32F) 

Answer 2

When you normalize a matrix using NORM_L1, you are dividing every pixel value by the sum of absolute values of all the pixels in the image. As a result, all pixel values become much less than 1 and you get a black image. Try NORM_MINMAX instead of NORM_L1.