图像金字塔一文中，已经详细介绍了图像金字塔的MATLAB实现，这里贴上OpenCV Python的实现以做补充。在OpenCV中，主要使用cv2.pyrDown和cv2.pyrUp两个函数，在没有指定输出图像的大小的情况下，下采样的图像尺寸会进行四舍五入。比如，189x189的图像会亚采样为95x95大小。为了保证在拉普拉斯金字塔和图像重建过程中的图像大小一致，下面的函数限制了下采样、上采样的输出图像大小（dstsize参数）。
import cv2
import numpy as np
def gaussian_pyr(img,lev):
img = img.astype(np.float)
g_pyr = [img]
cur_g = img;
for index in range(lev):
print(index)
cur_g = cv2.pyrDown(cur_g)
g_pyr.append(cur_g)
return g_pyr
def laplacian_pyr(img,lev):
img = img.astype(np.float)
g_pyr = gaussian_pyr(img,lev)
l_pyr = []
for index in range(lev):
cur_g = g_pyr[index]
cur_w,cur_h = np.shape(cur_g)
next_g = cv2.pyrUp(g_pyr[index+1],dstsize=(cur_h,cur_w))
cur_l = cv2.subtract(cur_g,next_g)
l_pyr.append(cur_l)
l_pyr.append(g_pyr[-1])
return l_pyr
def lpyr_recons(l_pyr):
lev = len(l_pyr)
cur_l = l_pyr[-1]
for index in range(lev-2,-1,-1):
#print(index)
next_w,next_h = np.shape(l_pyr[index])
cur_l = cv2.pyrUp(cur_l,dstsize=(next_h,next_w))
next_l = l_pyr[index]
cur_l = cur_l + next_l
return cur_l
对上面函数的测试：
#from Uti.pyr import *
#from Uti.utis import *
import imageio
import matplotlib.pyplot as plt
img = imageio.imread('LENA.JPG')
img = luminance(img)
m = gaussian_pyr(img,5)
for i in range(len(m)):
plt.imshow(m[i],cmap='gray')
plt.show()
g = laplacian_pyr(img,5)
for i in range(len(g)):
plt.imshow(g[i],cmap='gray')
plt.show()
t = lpyr_recons(g)
plt.imshow(t,cmap='gray')
plt.show()
