问在Python中按K因子缩放图像的最简单算法

EN

# loading the image
from PIL import Image
import numpy as np
image = np.asarray( Image.open("img.jpg") )
import matplotlib.pyplot as plt

# create new image of correct size
m = len(image[0])
n = len(image)
factor = 3
new_image = np.zeros((factor*(n-1) + 1,factor*(m-1) + 1,3), dtype=int)

# implement row zooming
for i in range(n):
    row = image[i]
    for k in range(len(row)-1):
        new_image[i][k*factor], new_image[i][(k+1)*factor] = row[k], row[k+1]
        for mode in range(3):
            # need mode as three colour channels in RGB

            lo = int(min(row[k][mode], row[k+1][mode]))
            hi = int(max(row[k][mode], row[k+1][mode]))
            diff = int((hi-lo)//factor)
            for x in range(factor-1):
                new_image[i][k*factor+1+x][mode] = lo + (x*diff)

from PIL import Image
import numpy as np
image = np.asarray( Image.open("lenna.png") )
import matplotlib.pyplot as plt
plt.imshow(image)
plt.show()

# Simply increase the resolution of the image by repeating the pixels
zoom_factor = 3
for i in range(2):
    image = np.repeat(image, zoom_factor, axis=i)

# Focus on any paricular region by croping it out
image = image[700:1000, 700:1000]
plt.imshow(image)
plt.show()