函数说明

cv2.addWeighted(src1, alpha, src2, beta, gamma[, dst[, dtype]]) → dst

• 1

参数说明

• src1 – first input array.
• alpha – weight of the first array elements.
• src2 – second input array of the same size and channel number as src1.
• beta – weight of the second array elements.
• dst – output array that has the same size and number of channels as the input arrays.
• gamma – scalar added to each sum.
• dtype – optional depth of the output array; when both input arrays have the same depth, dtype can be set to -1, which will be equivalent to src1.depth().

此函数可以用一下矩阵表达式来代替：

dst = src1 * alpha + src2 * beta + gamma;

注意：由参数说明可以看出，被叠加的两幅图像必须是尺寸相同、类型相同的；并且，当输出图像array的深度为CV_32S时，这个函数就不适用了，这时候就会内存溢出或者算出的结果压根不对。

CV_32S is a signed 32bit integer value for each pixel

python代码实现:

# coding=utf-8

import cv2

# 底板图案

bottom_pic = 'girl1.jpg'

# 上层图案

top_pic = 'girl2.jpg'

bottom = cv2.imread(bottom_pic)

top = cv2.imread(top_pic)

h, w, _ = bottom.shape

img2 = cv2.resize(top, (w,h), interpolation=cv2.INTER_AREA)

#alpha，beta，gamma可调

alpha = 0.7

beta = 1-alpha

gamma = 0

# 权重越大，透明度越低

overlapping = cv2.addWeighted(bottom, alpha, img2, beta, gamma)

#cv2.addWeighted(bottom, 0.5, img2, 0.5, 0)

#overlapping = cv2.addWeighted(bottom,0.8,top,0.2,0)

# 保存叠加后的图片

cv2.imwrite('overlap(8:2).jpg', overlapping)

cv2.namedWindow('newImage')

cv2.imshow('newImage',overlapping)

cv2.waitKey()

cv2.destroyAllWindows()