A New Anisotropic Diffusion Equation with Adaptive Fidelity Term

2007 ◽  
Author(s):  
Xiaoli Sun ◽  
Guoxiang Song
Keyword(s):  
Diffusion Equation ◽  
Anisotropic Diffusion ◽  
Fidelity Term ◽  
Anisotropic Diffusion Equation

scholarly journals Nonlocal Adaptive Image Denoising Model

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Xiaoli Sun ◽  
Chen Xu ◽  
Min Li
Keyword(s):  
Diffusion Equation ◽  
Anisotropic Diffusion ◽  
Diffusion Tensor ◽  
Gaussian Function ◽  
Nonlocal Diffusion ◽  
Gaussian Kernel ◽  
Diffusion Term ◽  
Obvious Effect ◽  
Fidelity Term ◽  
Anisotropic Diffusion Equation

When denoising with the method of Weickert’s anisotropic diffusion equation, the textures and details will be compromised. A fidelity term is added to Weickert’s equation, and the coefficient of fidelity term will vary adaptively with the instant image, which makes the diffusion term and the fidelity term come to a better compromise. Otherwise, when deciding the edge directions, because of the strong smoothness of linear Gaussian function, a few other edge directions hiding in the main direction will be lost. To preserve these detailed edge directions, Gaussian kernel is substituted for nonlinear wavelet threshold. In addition, in order to preserve the textures and details as much as possible, a nonlocal diffusion tensor was introduced, and the two eigenvalues are reset by combining the two methods: edge-enhancing diffusion and coherence-enhancing diffusion. Experiments show that the new model has an obvious effect on preserving textures and details.

scholarly journals An image super-resolution reconstruction model based on fractional-order anisotropic diffusion equation

2021 ◽  
Vol 18 (5) ◽  
pp. 6581-6607
Author(s):  
Jimin Yu ◽  
◽  
Jiajun Yin ◽  
Shangbo Zhou ◽  
Saiao Huang ◽  
...  
Keyword(s):  
Diffusion Equation ◽  
Image Denoising ◽  
Anisotropic Diffusion ◽  
Super Resolution ◽  
New Model ◽  
Staircase Effect ◽  
Washout Filter ◽  
Image Super Resolution ◽  
Fidelity Term ◽  
Anisotropic Diffusion Equation

<abstract><p>The image denoising model based on anisotropic diffusion equation often appears the staircase effect while image denoising, and the traditional super-resolution reconstruction algorithm can not effectively suppress the noise in the image in the case of blur and serious noise. To tackle this problem, a novel model is proposed in this paper. Based on the original diffusion equation, we propose a new method for calculating the adaptive fidelity term and its coefficients, which is based on the relationship between the image gradient and the diffusion function. It is realized that the diffusion speed can be slowed down by adaptively changing the coefficient of the fidelity term, and it is proved mathematically that the proposed fractional adaptive fidelity term will not change the existence and uniqueness of the solution of the original model. At the same time, washout filter is introduced as the control item of the model, and a new model of image super-resolution reconstruction and image denoising is constructed. In the proposed model, the order of fractional differential will be determined adaptively by the local variance of the image. And we give the numerical calculation method of the new model in the frequency domain by the method of Fourier transform. The experimental results show that the proposed algorithm can better prevent the staircase effect and achieve better visual effect. And by introducing washout filter to act as the control of the model, the stability of the system can be improved and the system can converge to a stable state quickly.</p></abstract>

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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