convert images from [-1; 1] to [0; 255]

Question

I know that question is really simple, but I didn't find how to bypass the issue:

I'm processing images, the output pixels are float32, and values are in range [-1; 1]. The thing is, when saving using openCV, all negative data and float values are lost (I only get images with 0 or 1 values)

So I need to convert those images to [0; 255] (Int8)

I've tried

• img * 255, but doing this does not help with negative values.
• (img + 1) * 255, I'm removing the negative values, but I'm creating an overflow

Is there a (clean) way to do it ?

I'm using Python35, OpenCV2 and Numpy, but I think it's more a math problem than a library thing

Answer 1

You can use cv2.normalize()

Consider the following array a:

a = np.array([[-0.12547205, -1.        ],
              [ 0.49696118,  0.91790167],
              [ 0.81638017,  1.        ]])

norm_image = cv2.normalize(image, None, alpha = 0, beta = 255, norm_type = cv2.NORM_MINMAX, dtype = cv2.CV_32F)

norm_image = norm_image.astype(np.uint8)

norm_image returns the following array:

array([[111,   0],
      [190, 244],
      [231, 255]], dtype=uint8)

In this example:

• -1 will be mapped to 0
• 1 will be mpped to 255
• Everything in between will be mapped accordingly (0, 255)

Points to note:

1. Ensure the array is of type float
2. The extreme of values are place in alpha and beta respectively.