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Description: ％ A 2D homogeneous convection-diffusion case (u=exp(-ex*deta*x-ex*deta*y) with a square with
％ all Dirichlet boundary, note that reaction coefficient is not zero
％ by indirect BKM
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Size: 2446 |
Author: 项羽 |
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Description: matlab的十几种图像滤波算法，费好大力气才找到的，希望能给于借鉴-several image filtering algorithm, spent many great efforts to find, in the hope that they will learn from
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Size: 179200 |
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Description: ％ A 2D homogeneous convection-diffusion case (u=exp(-ex*deta*x-ex*deta*y) with a square with
％ all Dirichlet boundary, note that reaction coefficient is not zero
％ by indirect BKM - A 2D homogeneous convection-diffusion case (u = exp (-ex* deta* x-ex* deta* y) with a square with all Dirichlet boundary, note that reaction coefficient is not zero by indirect BKM
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Size: 2048 |
Author: 项羽 |
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Description: 当前论文主要考虑的是非信号依赖的高斯噪声下的图像恢复，本程序实现了泊松噪声下的图像恢复，泊松噪声为信号依赖噪声，能够更加有效逼近实际成像系统噪声。- This is the code that was used in the papers "A Nonnnegatively Constrained Convex Programming Method for Image Reconstruction", "Total Variation-Penalized Poisson Likelihood Estimation for Ill-Posed Problems", "Tikhonov Regularized Poisson Likelihood Estimation: Theoretical Justification and a Computational Method", "An Efficient Computational Method for Total Variation with Poisson Negative-Log Likelihood", "An Analysis of Regularization by Diffusion for Ill-Posed Poisson Likelihood Estimation," "An Iterative Method for Edge-Preserving MAP Estimation when Data-Noise is Poisson", and finally, "Regularization Parameter Selection Methods for Ill-Posed Poisson Maximum Likelihood Estimation". See my publications page for more details. The main algorithm is for nonnegatively constrained, regularized Poisson likelihood estimation. At this point you can choose Tikhonov, total variation regularization, and diffusion regularization. A number of other methods are also implemented. Regularizatio
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Size: 432128 |
Author: sun |
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Description: Image Edge Enhancing Coherence Filter Toolbox，各向异性非线性扩散滤波器-This toolbox will perform Anisotropic Non-Linear Diffusion filtering on a 2D gray/color or 3D image. This filtering will reduce the image noise while preserving the region edges, and also enhancing the edges by smoothing along them.
This is one of the more advanced image enhancement methods available, and also contains HDCS from october 2009. The result looks like an artist painted the image, with clear brush strokes along the image edges and ridges, see screen-shot.
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Size: 1437696 |
Author: 陈翼男 |
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