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3下载：
全变差求解病态线性方程组的算法说明及其Matlab上的实现代码，在反演问题中常常会用到，全变差正则化具有边界识别强的特点，在图像去噪和恢复方面很有价值！-Total Variation solving ill-conditioned linear equations Matlab algorithm descr iption and implementation code on the inverse problem will often be used, total variation reg
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基于全变分的图像复原算法，附有实验图片，对初学图像复原的学者有很大的帮助！-Image restoration algorithm based on total variation, accompanied by the experimental images, is of great help to beginners image restoration scholar!
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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
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课题要求系统分析整体变分（TV）修复模型在图像修复中的应用，并在此基础上实现基于TV模型的图像修复算法，最后对仿真结果进行分析。-Topics for system analysis and total variation (TV) repair model in the application of image restoration, and on this basis to realize the image restoration algorithm based on TV model,
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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
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是基于变分的方法，此类方法将图像处理领域的
问题用变分方法转化为某个泛函式的最小化问题，
最具代表性的变分去噪模型是总变差( Total Variation，
TV) 模型即TV 模型-Is based on the variational method, such methods to problems in image processing by variational methods into a pan function minimization problem, the m
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CV模型是一种重要的图像分割模型,本文针对其收敛速度慢、效率低的缺点提出一种求解CV模型的新方法.首先将CV模型的能量泛函改写成与原来有相同稳定解的总变分公式形式,然后使用对偶公式法求总变分公式的极小值,再在其中引入一速度项以加快模型的收敛速度.新方法一方面克服了梯度下降法要求时间步长小、迭代次数多的缺点,经过较少次的迭代就能收敛,减少了迭代计算的次数-CV model is one of the most important image segmentation model and disad
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基于图像总变分的图像恢复算法，对于被噪声模糊的图像具有很好地恢复效果。-Image image restoration algorithm based on total variation, the noise was blurred image with a good recovery effect.
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We propose a new class of models for image restoration and decomposition
by functional minimization. Following ideas of Y. Meyer in a total variation minimization
framework of L. Rudin, S. Osher, and E. Fatemi, our model decomposes a
given (deg
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图像去噪经典模型，参考自Nonlinear total variation based noise removal algorithms-image denoising － TV
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matlab code
Proposed Algorithm
1. Consider the image to be resized to N x N (Original image I having N value of pixel)
2. Image is to be changed into gray and double for 2-D image.
3. Add noise to image using gaussian white filter.
4.
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We propose a new class of models for image restoration and decomposition
by functional minimization. Following ideas of Y. Meyer in a total variation minimization
framework of L. Rudin, S. Osher, and E. Fatemi, our model
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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~gray
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对于带噪声的周期性纹理图像,提出一种基于二维秩约束的混合正则化去噪方法。该方法结合了全变分去噪理论和方法，并且利用该类图像低块秩的特性，对图像进行了低块秩约束。通过和全变分去噪方法比较可知，对于周期性纹理图像，混合正则化方法能有效地分离出噪声，并且能让图像很好地保持边缘。即使非严格的周期性纹理，该方法依然有很好的去噪效果。-For periodic texture images with noise, a new method based on two dimensional rank cons
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基于全变差的视频图像压缩感知重构算法论文及代码-The image/video compressive sensing reconstruction algorithm based on total variation
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各向异性光谱空间总变异模型
用于多光谱遥感
图像去噪-nisotropic Spectral-Spatial Total Variation Model
for Multispectral Remote Sensing
Image Destriping
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对l1最小化的处理，其中包括全面的l1范数的解得算法，运用tv全变分最小的解决方法，适合于单像素以及图像处理的研究者参考。(L1 minimization, including the full L1 norm solution algorithm, the use of TV total variation, the smallest solution, suitable for single pixel and image processing researchers reference.)
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纹理识别，LTV，通过求梯度，进而求图像的局部总变差，对指纹图像进行纹理提取(Texture recognition, LTV, by seeking gradient, and then find the local image of the total variation, the fingerprint image texture extraction)
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全变分去卷积算法的matlab实现； 全变分算法的论文； 全变分实现超分辨；全变分实现图像去噪；全变分实现图像恢复(total variation deconvolution; the paper of TV; super resolution; denoising; image recover)
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基于总变差正则化模型的图像复原，有图像加噪去噪，去模糊的功能(Image restoration based on total variation regularization model has functions of image denoising, denoising and deblurring.)
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