How to morph two grid-like images seamlessly?

Question

I have two images that consist of colored squares with different grid step (10x10 and 12x12).

What I want is to make the first image to be smoothly transformed into the second one.

When I use a plain image overlay with cv2.addWeighted() function, the result (left) is not good because of the intersected grid spaces. I suppose it would be better to shift remaining grid cells to the borders and clear out the rest (right).

Is there any algorithm to deal with this task?

Thanks.

Answer 1

You can interpolate each pixel individually between different images.

import numpy as np
from scipy import interpolate
import matplotlib.pyplot as plt

np.random.seed(200)

num_images = 2
images = np.random.rand(num_images, 8,8)

for index, im in enumerate(images):
    print(f'Images {index}')
    fig = plt.imshow(im)
    plt.show()

Interpolating these images:

n_frames = 4
x_array = np.linspace(0, 1, int(n_frames))


def interpolate_images(frame):
    intermediate_image = np.zeros((1, *images.shape[1:]))
    for lay in range(images.shape[1]):
        for lat in range(images.shape[2]):
            tck = interpolate.splrep(np.linspace(0, 1, images.shape[0]), images[:, lay, lat], k = 1)
            intermediate_image[:, lay, lat] = interpolate.splev(x_array[frame], tck)
    return intermediate_image


for frame in range(n_frames):
    im = interpolate_images(int(frame))
    fig = plt.imshow(im[0])
    plt.show()