OpenCV+Python实现图像运动模糊和高斯模糊

OpenCV+Python实现图像运动模糊和高斯模糊

运动模糊： 由于相机和物体之间的相对运动造成的模糊，又称为动态模糊

OpenCV+Python实现运动模糊，主要用到的函数是cv2.filter2D()：

# coding: utf-8
import numpy as np
import cv2

def motion_blur(image, degree=12, angle=45):
    image = np.array(image)

    # 这里生成任意角度的运动模糊kernel的矩阵， degree越大，模糊程度越高
    M = cv2.getRotationMatrix2D((degree / 2, degree / 2), angle, 1)
    motion_blur_kernel = np.diag(np.ones(degree))
    motion_blur_kernel = cv2.warpAffine(motion_blur_kernel, M, (degree, degree))

    motion_blur_kernel = motion_blur_kernel / degree
    blurred = cv2.filter2D(image, -1, motion_blur_kernel)

    # convert to uint8
    cv2.normalize(blurred, blurred, 0, 255, cv2.NORM_MINMAX)
    blurred = np.array(blurred, dtype=np.uint8)
    return blurred

img = cv2.imread('linuxboy.net.jpg')
img_ = motion_blur(img)

cv2.imshow('Source image',img)
cv2.imshow('blur image',img_)
cv2.waitKey()

原图与运动模糊效果如下：

高斯模糊：图像与二维高斯分布的概率密度函数做卷积，模糊图像细节

OpenCV+Python实现高斯模糊，主要用到的函数是cv2.GaussianBlur():

# coding: utf-8
import numpy as np
import cv2

img = cv2.imread('linuxboy.net.jpg')
img_ = cv2.GaussianBlur(img, ksize=(9, 9), sigmaX=0, sigmaY=0)

cv2.imshow('Source image',img)
cv2.imshow('blur image',img_)
cv2.waitKey()

高斯模糊效果如下：

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