OpenCV Python实现图像金字塔

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()