The evaluation of image saliency based on Laplacian operator can easily distinguish the focus region and out of focus region. And the decision map obtained by Laplacian operator processing has less the residual information than other methods. For getting precise decision map, focus area and edge ...
The Laplacian operator is a template in computer science that implements second-order differencing by computing the difference between a point and the average of its four direct neighbors. It is used for edge detection and image processing, but requires additional smoothing to handle noise effectively...
grayImage=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)#Roberts算子 kernelx=np.array([[-1,0],[0,1]],dtype=int)kernely=np.array([[0,-1],[1,0]],dtype=int)x=cv2.filter2D(grayImage,cv2.CV_16S,kernelx)y=cv2.filter2D(grayImage,cv2.CV_16S,kernely)#转uint8 absX=cv2.convertScaleAbs(x)a...
The Laplacian operator is widely used in edge detection in image processing. (拉普拉斯算子在图像处理中的边缘检测方面得到了广泛应用。) The Laplacian matrix of a graph represents the adjacency and degree information of the graph. (一个图的拉普拉斯矩阵表示了图的邻接度和度信息。) Laplacian smoothing ...
In image processing, a Laplacian filter is a type of edge detection filter that is commonly used to enhance the edges of an image. It is based on the Laplacian operator, which is a second-order derivative operator that highlights rapid intensity changes in an image. In this article, we wil...
Saoudi, K., Ghanmi, A.: A multiplicity results for a singular equation involving the p(x)-Laplace operator. Complex Var. Elliptic Equ. 62, 695–725 (2017) Article MathSciNet Google Scholar Wang, L., Zhang, B.: Infinitely many solutions for Kirchhoff-type variable-order fractional Laplac...
Image Processingedge detectionSchwartz inequalitygradient sum and max operatorsSobel and Prewitt masksThis note introduces componentwise edge detection technique for Laplacian operator masks. Laplacian operator masks are expressed by means of gradient components. The absolute sums of the gradient components ...
Lattice reaction-diffusion models such as (2) are investigated in the literature [10] mostly using energy methods. This contrasts with PDE versions like (1) which use mild solutions and the semi-group operator represented symbolically as the exponential of the Laplacian operator, see e.g., Henr...
spherical topology. Third, we show that algorithms used for each individual step of the analysis pipeline (cell segmentation, topology fixing, spherical parameterization, and shape representation) are closely related to the Laplacian operator. The framework is applied to the shape analysis of neutrophil...
Operator Theory Partial Differential Equations Diffusion Processes and Stochastic Analysis on Manifolds Functional Analysis Partial Differential Equations on Manifolds 1Introduction Methods for image processing, data analysis and simulation of information propagation have strongly benefited from using graph structures...