Opencv Python 简明教程

OpenCV Python - Image Blending with Pyramids

通过使用图像金字塔可以最大程度减少图像的不连续性。这将产生无缝融合的图像。

The discontinuity of images can be minimised by the use of image pyramids. This results in a seamless blended image.

采取以下步骤来实现最终结果 −

Following steps are taken to achieve the final result −

首先加载图像并为两幅图像寻找高斯金字塔。以下是执行此操作的程序 -

First load the images and find Gaussian pyramids for both. The program for the same is as follows −

import cv2
import numpy as np,sys

kalam = cv2.imread('kalam.jpg')
einst = cv2.imread('einstein.jpg')
### generate Gaussian pyramid for first
G = kalam.copy()
gpk = [G]
for i in range(6):
   G = cv2.pyrDown(G)
   gpk.append(G)
# generate Gaussian pyramid for second
G = einst.copy()
gpe = [G]
for i in range(6):
   G = cv2.pyrDown(G)
   gpe.append(G)

从高斯金字塔获取相应的拉普拉斯金字塔。以下是执行此操作的程序 -

From the Gaussian pyramids, obtain the respective Laplacian Pyramids. The program for the same is as follows −

# generate Laplacian Pyramid for first
lpk = [gpk[5]]
for i in range(5,0,-1):
   GE = cv2.pyrUp(gpk[i])
   L = cv2.subtract(gpk[i-1],GE)
   lpk.append(L)

# generate Laplacian Pyramid for second
lpe = [gpe[5]]
for i in range(5,0,-1):
   GE = cv2.pyrUp(gpe[i])
   L = cv2.subtract(gpe[i-1],GE)
   lpe.append(L)

然后，在金字塔中的每个层中将第一张图像的左半部分与第二张图像的右半部分结合在一起。因此，该程序如下所示 −

Then, join the left half of the first image with the right half of second in each level of pyramids. The program for the same is as follows −

# Now add left and right halves of images in each level
LS = []
for la,lb in zip(lpk,lpe):
   rows,cols,dpt = la.shape
   ls = np.hstack((la[:,0:int(cols/2)], lb[:,int(cols/2):]))
   LS.append(ls)

最后，从这个联合金字塔中重建图像。因此，该程序如下所示 −

Finally, reconstruct the image from this joint pyramid. The program for the same is given below −

ls_ = LS[0]
for i in range(1,6):
   ls_ = cv2.pyrUp(ls_)
   ls_ = cv2.add(ls_, LS[i])
   cv2.imshow('RESULT',ls_)

Output

混合后的结果应如下所示 −

The blended result should be as follows −

blending pyramids