图像金字塔原理

expand = 扩大+卷积

拉普拉斯金字塔

PyrDown：降采样

PyrUp：还原

example

import cv2 as cv

import numpy as np

# 图像金字塔和拉普拉斯金字塔(L1 = g1 - expand(g2))：reduce：高斯模糊+降采样，expand：扩大+卷积

# PyrDown降采样，PyrUp还原

def pyramid_demo(image):

    level = 4

    temp = image.copy()

    pyramid_images = []

    for i in range(level):

        dst = cv.pyrDown(temp)

        pyramid_images.append(dst)

        cv.imshow("pyramid_down_"+str(i+1), dst)

        temp = dst.copy()

    return pyramid_images

def laplace_demo(image):  # 注意：图片必须是满足2^n这种分辨率

    pyramid_images = pyramid_demo(image)

    level = len(pyramid_images)

    for i in range(level-1, -1, -1):

        if i-1 < 0:

            expand  = cv.pyrUp(pyramid_images[i], dstsize=image.shape[:2])

            lpls = cv.subtract(image, expand)

            cv.imshow("laplace_demo"+str(i), lpls)

        else:

            expand = cv.pyrUp(pyramid_images[i], dstsize=pyramid_images[i-1].shape[:2])

            lpls = cv.subtract(pyramid_images[i-1], expand)

            cv.imshow("laplace_demo"+str(i), lpls)

if __name__ == '__main__':

    src = cv.imread("../images/lena.jpg")  # 读入图片放进src中

    cv.imshow("demo", src)  # 将src图片放入该创建的窗口中

    # pyramid_demo(src)

    laplace_demo(src)

    cv.waitKey(0) # 等有键输入或者1000ms后自动将窗口消除，0表示只用键输入结束窗口

    cv.destroyAllWindows()  # 关闭所有窗口