下面是Python/OpenCV中的一种方法。

• 读取每张图像
• 将圆形图像转换为灰度
• 对圆形图像设置阈值
• 将第二个图像裁剪为第一个图像的大小
• 使用阈值图像作为要使用的区域的选择符来合并裁剪的第二图像与第一图像
• 保存结果

输入1：

输入2：

import cv2
import numpy as np

# read image 1
img1 = cv2.imread('white_circle.png')
h1, w1 = img1.shape[:2]

# read image 2
img2 = cv2.imread('bear_heart.jpg')
h2, w2 = img2.shape[:2]

# convert img1 to grayscale
gray = cv2.cvtColor(img1, cv2.COLOR_BGR2GRAY)

# threshold to binary
thresh = cv2.threshold(gray, 254, 255, cv2.THRESH_BINARY)[1]
thresh = cv2.cvtColor(thresh, cv2.COLOR_GRAY2BGR)

# crop second image to size of first image
img2_crop = img2[0:h1, 0:w1]

# combine img1, img2_crop with threshold as mask
result = np.where(thresh==255, img2_crop, img1)

# save results
cv2.imwrite('white_circle_thresh.jpg', thresh)
cv2.imwrite('white_circle_bear_heart.jpg', result)

cv2.imshow("thresh", thresh)
cv2.imshow("result", result)
cv2.waitKey(0)
cv2.destroyAllWindows()

阈值图像：

结果图像：