Numerical analysis of AOR iteration for anisotropic diffusion equation in image blurring

2018 ◽  
Author(s):  
N. A. Basran ◽  
J. H. Eng ◽  
A. Saudi ◽  
J. Sulaiman
Keyword(s):  
Numerical Analysis ◽  
Diffusion Equation ◽  
Anisotropic Diffusion ◽  
Image Blurring ◽  
Anisotropic Diffusion Equation

scholarly journals Application of Image Recognition Method Based on Diffusion Equation in Film and Television Production

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Liyuan Guo
Keyword(s):  
Diffusion Equation ◽  
Diffusion Model ◽  
Image Recognition ◽  
Anisotropic Diffusion ◽  
Speckle Noise ◽  
Camera Motion ◽  
Film And Television ◽  
Similarity Calculation ◽  
Image Noise Reduction ◽  
Anisotropic Diffusion Equation

On the basis of studying the basic theory of anisotropic diffusion equation, this paper focuses on the application of anisotropic diffusion equation in image recognition film production. In order to further improve the application performance of P-M (Perona-Malik) anisotropic diffusion model, an improved P-M anisotropic diffusion model is proposed in this paper, and its application in image ultrasonic image noise reduction is discussed. The experimental results show that the model can effectively suppress the speckle noise and preserve the edge features of the image. Based on the image recognition technology, an image frame testing system is designed and implemented. The method of image recognition diffusion equation is used to extract and recognize the multilayer feature points of the test object according to the design of artificial neural network. To a certain extent, it improves the accuracy of image recognition and the audience rating of film and television. Use visual features of the film and television play in similarity calculation for simple movement scene segmentation problem, at the same time, the camera to obtain information, use the lens frame vision measuring the change of motion of the camera, and use weighted diffusion equation and the visual similarity of lens similarity calculation and motion information, by considering the camera motion of image recognition, effectively solve the sports scene of oversegmentation problem such as fighting and chasing.

Skeletonization of Edges Extracted by Natural Images

2015 ◽  
pp. 146-185
Author(s):  
Donatella Giuliani
Keyword(s):  
Steady State ◽  
Diffusion Equation ◽  
Force Field ◽  
Real World ◽  
Anisotropic Diffusion ◽  
Binary Images ◽  
External Force Field ◽  
Anisotropic Diffusion Equation ◽  
Simply Connected ◽  
Boundary Perturbations

This chapter presents a method to compute the skeletal curve of shapes extracted by images derived by the real world. This skeletonization approach has been proved effective when applied to recognize biological forms, regardless of their complexity. The coloured and grayscale images have been pre-processed and transformed in binary images, recurring to segmentation. Generally the resulting binary images contain bi-dimensional bounded shapes, not-simply connected. For edge extraction it has been performed a parametric active contour procedure with a generalized external force field. The force field has been evaluated through an anisotropic diffusion equation. It has been noticed that the field divergence satisfies an anisotropic diffusion equation as well. Moreover, the curves of positive divergence can be considered as propagating fronts that converge to a steady state, the skeleton of the extracted object. This methodology has also been tested on shapes with boundary perturbations and disconnections.

Infrared Dim and Small Target Detection Algorithm Based on Multi-scale Anisotropic Diffusion Equation

2015 ◽  
Vol 44 (9) ◽  
pp. 910002 ◽  
Author(s):  
周慧鑫 ZHOU Hui-xin ◽  
赵营 ZHAO Ying ◽  
秦翰林 QIN Han-lin ◽  
殷世民 YIN Shi-min ◽  
刘刚 LIU Gang ◽  
...  
Keyword(s):  
Diffusion Equation ◽  
Target Detection ◽  
Anisotropic Diffusion ◽  
Detection Algorithm ◽  
Small Target ◽  
Small Target Detection ◽  
Multi Scale ◽  
Anisotropic Diffusion Equation
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