示例11: LaplacianOfGaussian ▲点赞 5▼ # 需要导入模块: import cv2 [as 别名]# 或者: from cv2 importLaplacian[as 别名]defLaplacianOfGaussian(image):LoG_image = cv2.GaussianBlur(image, (3,3),0)# paramtergray = cv2.cvtColor( LoG_image, cv2.COLOR_BGR2GRAY) LoG_image = cv2.Laplacian( gra...
LOG(Laplacian of Gaussian)边缘检测算子是David Courtnay Marr和 Ellen Hildreth在 1980年共同提出,也称为 Marr & Hildreth算子。它根据图像的信噪比来求检测边缘的最优滤波器。下面学习一下其原理和应用。2.2.1 LOG算子原理LOG算子首先对图像做高斯滤波,然后再求其拉普拉斯(Laplacian)二阶导数,根据二阶导数的锅零点...
defapplygaussian(imgs):gauss_f=call2dtensorgaussfilter()gauss_f=tf.expand_dims(gauss_f,axis=2)gauss_f=tf.expand_dims(gauss_f,axis=3)result=tf.nn.conv2d(imgs,gauss_f*4,strides=[1,1,1,1],padding="VALID")result=tf.squeeze(result,axis=0)result=tf.squeeze(result,axis=2)returnresult ...
public static Double calcSharpnessScore(Mat srcImage) { /// Remove noise with a Gaussian filter Mat filteredImage = new Mat(); Imgproc.GaussianBlur(srcImage, filteredImage, new Size(3, 3), 0, 0, BORDER_DEFAULT); int kernel_size = 3; int scale = 1; int delta = 0; Mat lplImage =...
Laplacian(img,cv2.CV_64F, ksize=5) # gaussian blur blur = cv2.GaussianBlur(img,(5,5),0) # laplacian of gaussian log = cv2.Laplacian(blur,cv2.CV_64F, ksize=5) # res = np.hstack([img, x_sobel, y_sobel]) # plt.imshow(res, cmap='gray') # plt.axis('off') # plt.show()...
Bilateral filter is used for reducing various noises especially Additive White Gaussian Noise which occur more in standard test images. The important feature of this nonlinear bilateral filter is the preservation of the edges, while reducing the noise in the images. The main idea is to replace ...
mkGaussian.m mkImpulse.m mkR.m mkRamp.m mkSine.m mkSquare.m mkZonePlate.m modulateFlip.m namedFilter.m nextFig.m pgmRead.m pgmWrite.m pixelAxes.m pointOp.m pointOp.mexa64 pointOp.mexglx pointOp.mexmac pointOp.mexmaci64 pointOp.mexw32 ...
This should be set to the sum of the kernel taps of the lowpass filter used to construct the pyramid (default assumes L2-normalized filters, using a value of 2 for 2D images, sqrt(2) for 1D images). Gpyr(image, height, filter, edges) Gaussian pyramid (subclass of Lpyr). image ...
图像边缘是图像最基本的特征,所谓边缘(Edge) 是指图像局部特性的不连续性。灰度或结构等信息的突变处称之为边缘。例如,灰度级的突变、颜色的突变,、纹理结构的突变等。边缘是一个区域的结束,也是另一个区域的开始,利用该特征可以提取图像边缘。 图(a)是一个理想的边缘所具备的特性。每个灰度级跃变到一个垂直的台...
Figure 1. The schematic framework of the proposed technique. At the core of the FLLF technique lies the Laplacian pyramid. This pyramid is constructed by generating a series of Gaussian pyramids of varying scales and then computing the differences between consecutive levels. Mathematically, for a...