Same shape Numpy arrays have different memory size

Question

I'm using PIL to import an image and transform it into a Numpy array, of shape (369, 103, 4). I then normalize the data and save both arrays. But when I do, the first image has a memory size of 149 KB, while the normalized one is 1.188 KB. How is that possible? How can I modify my code so that I don't end up with data almost x10 times the size of the original? The code I use is as follows:

from PIL import Image
import numpy as np
import os


path = os.getcwd()
temp = Image.open('{}/someimage.png'.format(path))
imagedata = np.asarray(temp)


def NormalizeData(data):
    return (data - np.min(data)) / (np.max(data) - np.min(data))

imagedata2 = NormalizeData(imagedata)

np.save('firstimage.npy', imagedata)
np.save('secondimage.npy', imagedata2)