搜索资源列表
variational_PDE_tools
- 变分偏微分方程图像处理工具包，包括计算曲率，方差，L1,L2范数等29个实用算法-variational PDE image processing tool kit, including the calculation of curvature, variance, L1, L2 norm, and other practical algorithms 29
Perona_Malik
- 图像的各向异性扩散，利用matlab实现Perona_Malik算法，梯度阈值K通过对图像求解2-范数的方法迭代获得-Anisotropic diffusion images, using matlab to achieve Perona_Malik algorithm, the gradient threshold images by solving the K 2- norm method will be obtained
Total_variation-regularized
- 总变分正则化超分辨率重建 包括两种范数形式的正则化-Total Variation Regularized super-resolution reconstruction, including two-norm in the form of regularization
conjugategrads
- 图像重建常常被转化为解非线性无约束极值问题, 通过范数极小化推导出共扼梯度法的 一般算法。通过对模拟数据和实际工件断层扫描数据进行图像重建, 估计了算法的有效性, 结果表明, 与最速下降法相比, 此算法更适用于不完全投影数据的图像重建, 在保证重建图像拟合度的同时, 大大提高了重建速度。-Image reconstruction has often been transformed into solving nonlinear unconstrained extremum problem,
MPEG2-AVI
- The development is based on MSSG MPEG2Decode 1. GUI interface (gui.cpp) 2. VFAPI support (vfapi.c vfapidec.c) 3. AC3/MPA/LPCM demux (getbit.c) 4. Auto-split AVI output through RGB24/YUY2 (store.c) 5. YUY2 DirectDraw Overlay (store.c gu
digitalimageprocessing
- 数字图像处理附带的源码，风格较规范，可以当做数字图像处理入门、新手练习-Digital image processing incidental source, style than the norm, as a digital image processing can be started, new practice
irntv
- TV正则化去卷积the Iteratively Reweighted Norm algorithm for solving the generalized TV functional, which includes the L2-TV and and L1-TV problems-An Iteratively Reweighted Norm Algorithm for Minimization of Total Variation Functionals
error2d
- Computes the FE error measured in the L2- and H1-norm for 2D problems. Especially useful for illustrating the error decay of piecewise linear finite elements in the common norms.
SAR-SIMULATION
- 图像的品质评定是图像处理领域的一项重要课题, 难以对其给出客观的评价. 文中引进模糊数学中的三角 模算子与非模糊基数等概念, 定义了数字图像模糊度. 理论与实验表明: 该定义比模糊指数更符合人眼的视觉特性, 并可用于评价图像品质. 图像模糊度能够明显提高图像处理系统的效率.-Image quality evaluation is an important field of image processing tasks, it is difficult Duiqi give an obje
An-adaptive
- 自适应正则化的超分辨率重建程序，采用L1L2范数。-Adaptive Regularized super-resolution reconstruction of the program, using L1L2 norm.
I
- 主要用于图像处理问题中的特征提取方面，是范数1的求解过程。-Mainly used in image processing of the problems of feature extraction, a norm the solving process of 1.
YALL1-v1.3
- 求解L1范数最小化问题的凸优化工具包，共含有6个模型的求解方法-Solving the L1-norm minimization problem of convex optimization toolkit contains a total of six methods of solving the model
Solvers
- 一范数问题的常见求解方法，广泛用于信号和图像处理当中。-some solvers fro l1-norm problem
Sobel
- 本算法是在经典Sobel算子基础上,结合汽车本身的实际情况,增加了6个方向模板,同时利用基于L2 范数的各同性扩散去噪模型消除噪声,最终得出汽车轮廓图。仿真结果表明:该算法对汽车图像的噪声干扰 有较强的抑制能力,汽车轮廓提取定位更准,精度更高,图像更清晰。-This algorithm is the classical Sobel operator on the basis of the actual situation with the car itself, an increase
SolveOMP
- OMP算法实现，主要用于重构,解决1范数问题，可以用于压缩感知-the complication of OMP algrithm to recovery，the maily function is to solve 1 norm question,it can be use in compressed sensing.
L1
- 基于L1范数的多帧图像超分辨率图像重建算法，在原有算法基础上改进，提高重建精度和效率。-Based on the L1 norm of the multi-frame image super-resolution image reconstruction algorithm, the improvement on the basis of the original algorithm to improve the reconstruction accuracy and efficiency.
L2
- 基于L2范数的多帧图像超分辨率图像重建算法，在现有算法基础上改进计算精度和效率。-Based on the L2 norm of the multi-frame image super-resolution image reconstruction algorithm, on the basis of existing algorithms to improve computational accuracy and efficiency.
l1_norm_compressed-sensing
- 两个l1准则下的噪声干扰信号压缩感知重构举例，两个例子的稀疏矩阵均为DCT矩阵，而观测矩阵分别采用单位阵和随机矩阵，有详细的步骤和使用方法，适用于初步的学习压缩感知方法。-This programme supply two examples by Compressed sensing with l1 norm. The sparse matrix of two examples are all DCT matrix and the obsever matrix are unit matrix a
KOMP
- 核稀疏表示的正交匹配追踪算法，这里核稀疏表示的正则化项为L0范数-Nuclear sparse representation orthogonal matching pursuit algorithm, where nuclear sparse representation regularization term is L0 norm
Matrix-Norm
- 本课件详细介绍了图像处理中的向量范数和矩阵范数的定义，并给出了相关应用。-The courseware details image processing vector norm and the matrix norm is defined, and gives related applications.