Python-OpenCV 图像叠加or图像混合加权实现
函数说明
cv2.addWeighted(src1, alpha, src2, beta, gamma[, dst[, dtype]]) → dst
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
代码:
def addImage(img1_path, img2_path):
img1 = cv2.imread(img1_path)
img = cv2.imread(img2_path)
h, w, _ = img1.shape
# 函数要求两张图必须是同一个size
img2 = cv2.resize(img, (w,h), interpolation=cv2.INTER_AREA)
#print img1.shape, img2.shape
#alpha,beta,gamma可调
alpha = 0.7
beta = 1-alpha
gamma = 0
img_add = cv2.addWeighted(img1, alpha, img2, beta, gamma)
cv2.namedWindow('addImage')
cv2.imshow('img_add',img_add)
cv2.waitKey()
cv2.destroyAllWindows()
img1:
img2:
叠加后结果:
(1)图1的权重为0.7,图二的权重为0.3, gamma为0 的结果:
img_add1
(2)图1的权重为0.7,图二的权重为0.3, gamma为100 的结果