搜索资源列表
S_R
- 图像稀疏表示源代码，实现输入图像的稀疏表示，有MOP,KSVD等算法-Matlab m-file code of Iamge Representation,it can run，contains MOP，KSVD.
Image-Sparse-Representation-Model
- 完备图像稀疏表示是一种最新的图像表示模型，采用过完备字典中原子的线性组合形式实现图像的稀疏表示．传统 的过完备图像稀疏表示模型采用重建误差的平方和作为保真项．该保真项没有充分考虑到人眼对图像的感知特性，无法度量图 像中边缘、轮廓、纹理等局部几何结构的变化．本文基于过完备稀疏表示理论思想，建立了新的稀疏性正则化的图像稀疏表示模 型．模型中的正则项约束图像表示系数的稀疏性，保真项采用更符合视觉感知的结构相似性度量．基于正交匹配追
KSVD_Color_IEEE_TIP
- 图像稀疏表示近来比较流行!本文是一篇基于k-svd方法变换的快速方法的经典文章！-Image sparse representation of the more popular lately! This article is based on a quick way to change the method of k-svd classic article!
HaarWare
- 基于哈小波的图像稀疏分解与重构。并进行MATLAB仿真。图像为经典lena图像-Image sparse decomposition and reconstruction based on wavelet. And the MATLAB simulation. The classic image to Lena image
omp
- 基于matlab仿真平台,快速匹配追踪OMP算法的图像稀疏分解与重构,并附带有OMP算法的详细讲解PPT-Based on the simulation platform of MATLAB, the fast matching pursuit (OMP) algorithm for image sparse decomposition and reconstruction. And with the OMP algorithm exp
dct
- 离散余弦变换dct算法详细讲解，并在matlab上进行图像稀疏分解与重建的图像处理仿真。-Discrete cosine transform DCT algorithm is explained in detail, and the simulation of image sparse decomposition and reconstruction of image processing in matlab.
xiaobo
- 基于小波变换的图像稀疏表示，用来进行图像去噪-Wavelet Transform for image sparse representation
eccv10-jtighe
- 基于超像素的可伸缩的非参数图像稀疏化 即超稀疏-SuperParsing: Scalable Nonparametric Image Parsing with Superpixels
Moving-Target-Detection-Method-
- 针对成像平台运动情况下的运动目标检测问题，提出了一种从特征点稀疏运动场估计到运动分类的目标检测算法。 首先通过快速特征点检测与跟踪恢复出图像稀疏运动场；然后依据特征点之间运动一致性关系实现属于同一运动模式的特征 点分类，根据分类得到的各组特征点计算场景图像重建误差，剔除重建误差最小的特征点组，实现对前景目标的检测。仿真实 验对该算法在复杂场景中检测运动目标的有效性进行了验证。-】In order to detect targ
S_R
- 对图像稀疏表示，可以运行出结果，MATLAB 图像稀疏表示代码，可以实现对输入图像的稀疏表示-Image sparse representation, you can run the results, MATLAB sparse representation code, can achieve a sparse representation of the input image
OMP
- 为了解决基于去噪重建过程，即解决稀疏系数原理的图像稀疏表示-In order to solve the reconstruction process based de-noising, that a solution to the sparse coefficient principle sparse representation
S_R
- matlab 压缩感知图像稀疏表示常见算法介绍及编码-matlab sparse
Wavelet_OMP
- 利用小波变换让图像稀疏化，正交匹配法实现重构-This procedure for the compression of the image LENA sensing, wavelet transform to image sparse algorithm using orthogonal matching method
incrementallearning_LCKSVD_shared
- 单幅图像超分辨处理 深度学习 稀疏表示 字典学习(Single image, super-resolution processing, depth learning, sparse representation, dictionary learning)
eccv10_tutorial_part2
- 稀疏编码图像分类, 稀疏表示创始人写的PPT,内容精彩,分析清晰,易于理解(sparse coding image classification, PPT written by the original author of sparse representation, the PPT content is easy to realize with clear illustration and analysis.)
mpfftimage
- 主要适用于做图像处理的稀疏分解程序，基于MP（匹配追踪）算法的稀疏分解程序一例(Mainly used for image processing sparse decomposition procedures, based on MP (matching pursuit) algorithm sparse decomposition procedures, for example)
SparseFusion_2014-12-03
- 基于稀疏表示的多光谱图像融合源代码，用于pansharpening(sparse-based mutispectral image fusion)
SRC
- 这是文章《Sparse Representation For Computer Vision and Pattern Recognition》的对应的稀疏表示代码，非原创，转载而来，供大家交流学习。(This is the code of SRC algorithm,and it's reproduced from others.)
K-SVD_and_W_KSVD_Sparse_Representation
- 通过字典学习更新的方法，对图像信号进行稀疏化分解(Through the method of learning and updating the dictionary, the image signals are sparse decomposed)
BPFA_Denoising
- 利用非参数贝叶斯字典学习模型进行图像稀疏表示(use non-parametric-bayesian-dictionary-learning-for-sparse-image-representations)