Description: 本程序实现全变分(Total Variation, TV)的去噪算法，它使用了PDF纠正TV算法中的小问题。该算法可以很好地保留原图边缘信息的同时，去除噪声。-This procedure Variational realize the whole (Total Variation, TV) denoising algorithm, which uses a PDF corrective TV algorithm of small problems. The algorithm is well positioned to retain the image edge information at the same time, to remove noise. Platform: |
Size: 44032 |
Author:zhuchangming |
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Description: 本程序实现全变分(Total Variation, TV)的去噪算法，它使用了PDF纠正TV算法中的小问题。该算法可以很好地保留原图边缘信息的同时，去除噪声。-This procedure to achieve full-variational (Total Variation, TV) denoising algorithm, which uses a PDF corrective TV algorithm of small problems. The algorithm is well positioned to retain the image edge information at the same time, to remove noise. Platform: |
Size: 1024 |
Author:Joe Black |
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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 Platform: |
Size: 432128 |
Author:sun |
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Description: 本程序实现全变分(Total Variation, TV)的去噪算法，它使用了PDF纠正TV算法中的小问题。该算法可以很好地保留原图边缘信息的同时，去除噪声。
-This procedure for full-variational (Total Variation, TV) denoising algorithm, which uses the PDF to correct TV algorithm small problem. This algorithm is well preserved, while Original edge information to remove noise. Platform: |
Size: 3072 |
Author:刘凯 |
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Description: 全变差图像处理，用的是分裂Bregman算法，可以很好地保留图像边缘，是目前研究者比较青睐的方法-Total variation image processing, using a split Bregman algorithm can well preserve the image edge, the researchers are currently more popular methods Platform: |
Size: 157696 |
Author:赵玲 |
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Description: 全变差模型和相位一致性结合提取图像的边缘信息，有效的处理了噪声的影响-Total variation model and the phase coherence combined edge image information extraction, effective treatment of the effects of noise Platform: |
Size: 654336 |
Author:wanghan |
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Description: 分析了基于整体变分（total variation,TV）模型的图像修复算法,TV模型修复算法只使用各向异性扩散,TV模型各向异性扩散仅向图像边缘方向扩散,容易在平滑区域引入阶梯效应。提出了一种改进的图像修复算法,该算法同时结合了各向同性和各向异性扩散,利用区域频率差异实现了在不同的区域使用不同的迭代方程,有效避免了原始算法引入的阶梯效应,同时在平滑区域提高了迭代效率。Matlab环境下的仿真结果表明,改进算法的修复效果和峰值信噪比的计算结果均明显优于原始算法-Analysis based on the total variation (total variation, TV) image restoration algorithm model behavior, TV model repair algorithm uses only anisotropic diffusion, TV model anisotropic diffusion diffusion only to the image edge direction, easy to introduce step effect in smooth areas. An improved image restoration algorithm, which combine both isotropic and anisotropic diffusion, use of regional difference in frequency enables the use of iterative equations different in different regions, effectively avoiding the staircase effect of the original algorithm introduced while smooth regions to improve iterative efficiency. Matlab environment simulation results show that the improved repair effect of the algorithm and the results were significantly better than the peak signal to noise ratio of the original algorithm Platform: |
Size: 272384 |
Author:毛巴马 |
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Description: 代码支持齐次线性和非线性（总变差和边缘增强流动）的任意尺寸领域各向同性扩散（标量/灰度图像，彩色图像和矩阵向量/结构张量）。添加剂算子分裂（AOS）以及高斯正则化的实现加速计算。-The code supports homogeneous and linear and nonlinear (Total Variation and Edge Enhancing flow) isotropic diffusion of arbitrary dimensioned fields(scalar~grayscale image, vector ~ color image and matrix~structure tensor). Additive Operator Splitting(AOS) as well as Gaussian regularization are implemented to speedup the computations. Platform: |
Size: 161792 |
Author:chi |
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Search - Total variation edge