opencv导向滤波

OpenCV中的导向滤波是通过cv.ximgproc.guidedFilter函数来实现的。这种算法的关键思想是盒式滤波（box filter），并且必须通过积分图来实现盒式滤波，以保证与窗口大小无关。

为了实现导向滤波算法，可以使用以下参考例程：

import cv2
import matplotlib.pyplot as plt

img = cv2.imread("../images/imgFabricNoise.png", flags=1)
imgGuide = cv2.imread("../images/imgFabric.png", flags=1)

imgGuidedFilter = cv2.ximgproc.guidedFilter(imgGuide, img, 10, 2, -1)

plt.figure(figsize=(9,6))
plt.subplot(131), plt.axis('off'), plt.title("Original")
plt.imshow(cv2.cvtColor(img, cv2.COLOR_BGR2RGB))
plt.subplot(133), plt.axis('off'), plt.title("cv2.guidedFilter")
plt.imshow(cv2.cvtColor(imgGuidedFilter, cv2.COLOR_BGR2RGB))
plt.tight_layout()
plt.show()

这段代码演示了如何使用cv2.ximgproc.guidedFilter函数对图像进行导向滤波处理。首先读取图像和引导图像，然后使用guidedFilter函数对图像进行滤波处理，最后显示原图和滤波结果。<span class="em">1</span><span class="em">2</span><span class="em">3</span>
#### 引用[.reference_title]
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