高斯差分金字塔python代码实现

高斯差分金字塔是一种图像金字塔的形式，它通过将图像进行不同程度的高斯模糊来构建。以下是使用 Python 实现高斯差分金字塔的代码示例：

import cv2
import numpy as np

def gaussian_pyramid(image, levels):
    pyramid = [image]
    for i in range(levels-1):
        image = cv2.pyrDown(image)
        pyramid.append(image)
    return pyramid

def laplacian_pyramid(gaussian_pyramid):
    pyramid = [gaussian_pyramid[-1]]
    for i in range(len(gaussian_pyramid)-1,0,-1):
        gaussian_expanded = cv2.pyrUp(gaussian_pyramid[i])
        laplacian = cv2.subtract(gaussian_pyramid[i-1], gaussian_expanded)
        pyramid.append(laplacian)
    pyramid.reverse()
    return pyramid

def gaussian_difference_pyramid(image, levels):
    gaussian = gaussian_pyramid(image, levels)
    laplacian = laplacian_pyramid(gaussian)
    difference_pyramid = []
    for i in range(levels-1):
        difference_pyramid.append(cv2.absdiff(gaussian[i+1], laplacian[i]))
    difference_pyramid.append(gaussian[-1])
    return difference_pyramid

# 读取图像
image = cv2.imread('image.jpg', 0)

# 构建高斯差分金字塔
levels = 4
difference_pyramid = gaussian_difference_pyramid(image, levels)

# 显示结果
for i in range(levels):
    cv2.imshow('Level {}'.format(i), difference_pyramid[i])
cv2.waitKey(0)
cv2.destroyAllWindows()

在上述代码中，我们首先定义了三个函数：

1. `gaussian_pyramid`：用于构建高斯金字塔。
2. `laplacian_pyramid`：用于构建拉普拉斯金字塔。
3. `gaussian_difference_pyramid`：用于构建高斯差分金字塔。

然后我们读入一张图像，并使用 `gaussian_difference_pyramid` 函数构建高斯差分金字塔。最后，我们使用 `cv2.imshow` 函数显示每个金字塔级别的结果。