原标题: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
importnumpy asnp
importcv2
defmotion_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)
returnblurred
img = cv2.imread( '.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
importnumpy asnp
importcv2
img = cv2.imread( '.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:
责任编辑: