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Untitled3
- 结合时空张量和总变差正则最小化的图像运动估计，以及超分辨率图像恢复-Combination of space-time tensor and the total variation is the smallest of the image motion estimation, as well as the super-resolution image restoration
MFTV
- 图像超分辨率程序，基于稀疏表示和正则化方法，程序带有注释，提供相关论文. 可以直接运行. -Matlab code about super-resolution, based on sparse representation and regularization. The codes include annotation. Related paper also provided
The-split-bregman-method
- 图像处理、Bregman迭代算法，分裂Bregman迭代算法，l1正则化问题-image processing,Bregman iteration,split Bregman iteration,l1-regularized problems
Distance-Regularized-Level-Set
- 水平集方法是一种先进的图像分割方法。这个matlab代码演示了一个基于边缘的活动轮廓模型，是下面一篇带距离正则化的水平集方程论文的应用： C. Li, C. Xu, C. Gui, M. D. Fox, Distance Regularized Level Set Evolution and Its Application to Image Segmentation , IEEE Trans. Image Processing, vol. 19 (12), pp. 3243-3254,
Nonlinear_Diffusion_v1.2
- 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
LowPatchRank_regularization
- 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
regularization
- 对图像进行正则化处理的matlab源程序，对学习正则化很有帮助-The image regularization process of matlab source code, learning regularization helpful
Image-deblurring-regularization
- Steve Eddins 所写的一篇关于运用正则化方法实现图像恢复的博客文章-Steve Eddins wrote an article about the use of regularization method of image restoration blog articles
Image-deblurring-
- 一份关于用正则化去除图像模糊的资料，内含代码以及说明，并附上了仿真结果图-A report on the Regularization blur removal image data containing codes and descr iptions, along with the simulation results of FIG.
ARKFCM_demo
- 脑图像分割基于自适应正则化的基于核的FCM分割，希望对大家有用-Brain Image Segmentation Based on Adaptive Regularization Based on Kernel FCM segmentation, we hope to be useful
SAR-Image-Despeckling
- 基于非局部正则化函数的合成孔径雷达图像斑点噪声去噪算法-SAR Image Despeckling by the Use of Variational Methods With Adaptive Nonlocal Functionals
CS_ROMP
- 压缩感知正则化正交匹配算法（ROMP）以及用此算法实现一维信号和二维图像的恢复，亲自编写调试可用-The ROMP algorithm for compressive sensing and using this method to reconstruct the 1D signal and 2D image.
dehaze
- 基于边界约束和上下文正则化的图像快速去雾算法-Effi cient Image Dehazing with Boundary Constraint and Contextual
public_code_ST
- 结构张量来进行自适应正则化图像重建，单幅图像重建-Structure tensor adaptive regularized image reconstruction, a single image reconstruction
deburring
- 基于多层紧框架变换的L0范数正则化图像去模糊-L0 norm regularized image deblurring based on multilayer compact frame transformation
An-efficient-augmented-
- 基于经典的增广拉格朗日乘子法, 对求解一类带有特定结构（主要是针对凸规划）的非光滑等式约束优化问题, 我们提出、分析并测试了一个新算法. 在极小化增广拉格朗日函数的每一步迭代中, 该算法有效结合了带有非单调线性搜索的交替方向技术, 我们建立了算法的收敛性, 并用它来求解在带有全变差正则化的图像恢复问题.-Based on the classic augmented Lagrangian multiplier method, we propose, analyze and test an algo
CSR_Denoising
- 该算法首先通过字典学习得到含噪图像的冗余字典，然后对相似的图像块进行聚类构成块群，并通过迭代收缩和L1正则化约束，对同类的图像块在字典上进行稀疏表示，以达到降噪的目的。实验结果表明，在常规的图像处理上，本文提出的算法能较好的保留图像的结构信息，与K-SVD和BM3D等现有的流行算法相比，具有更高的峰值信噪比（PSNR）-It firstly get the redundant dictionary of a noised image by dictionary learning.Then,the
BregmanCookbook_v32
- 这是用于l1正则化功能的bregman算法，主要用于图像去噪，去模糊，去卷积等(This is a Bregman algorithm for L1 regularization, which is mainly used for image denoising, blur, deconvolution, etc.)
adaptive TVMM demo
- 全变分图像反卷积:MAJORIZATION-MINIMIZATION方法。 《TOTAL VARIATION-BASED IMAGE DECONVOLUTION: A MAJORIZATION-MINIMIZATION APPROACH》这篇论文的源码 本文提出了一种新的在全变差正则化条件下图像反褶积的最大化-最小化算法。(Totally variational image deconvolution: The source of this paper TOTAL VARIATION-B
RL-TV
- 全变分正则化的RL算法matlab代码，同于图像非盲复原。