搜索资源列表
Image-restoration-algorithms
- 基于稀疏表达的图像恢复算法研究 对于研究图像恢复的程序员来说是一篇不错的参考文章-Image restoration algorithms based on sparse expression
ScSR
- Jianchao Yang 的基于稀疏表示的单幅图像重建的原始代码，先将高低训练图像分块，再将块训练成高低字典，将测试图像映射到低字典上，得到系数，再乘以高子典就得到最后的图像。对学习超分辨率同学的参考作用很大。-This is the original matlab code for super resolution by Jianchao Yang 。The method is sparse represent based on the overcomplete dictionary。
Image-reconstruction_CS
- 合稀疏贝叶斯学习(SBL)和可压缩传感理论(CS)，给出一种在噪声测量条件下重建可压缩图像的方法。该方法将cS理论中图像重建过程看作一个线性回归问题，而待重建的图像是该回归模型巾的未知权值参数；利用sBL方法对权值赋予确定的先验条件概率分布用以限制模型的复杂度，并引入超参数- Hop sparse Bayesian learning ( SBL ) and compressible sensing theory ( CS ) , give a compressible image recon
MP
- 稀疏表示的MP程序，已调试，可以直接使用哈！主要用于图像压缩，图像去噪等方面。-code for mp
L1-APG_release
- 最早将稀疏编码技术引入视频图像跟踪的L1跟踪器，2012年求解稀疏编码算法采用了新的计算方法。-The earliest will be sparse coding techniques L1 tracker, the introduction of the video image tracking the to solving sparse coding algorithm using a new calculation method in 2012.
omp
- 在图像的压缩感知方法中，用到了系数重构的思想，这里就是一种omp的稀疏重构算法。-Images compressed sensing method used coefficient remodeling ideas, here is a omp sparse reconstruction algorithm.
Gabor_toolbox
- gabor原子库工具箱,用于各种稀疏重构以及图像滤波等
APBT
- 代码使用全相位双正交变换（APBT）稀疏表示图像，主函数为test.-The code uses the all phase biorthogonal transform (APBT) sparse representation of the image, the main function for the test.
Image-Super-Resolution-Via-SR
- YANG JC 2010年基于稀疏表示的图像超分辨PPT，全英文-Yang JC 2010 super-resolution image based on sparse representation PPT, English
05466111
- 杨建超 基于稀疏表示的图像超分辨 2010年文章-YANG JC Image Super-Resolution Via Sparse Representation
text_lena1
- 这是本人编写的OMP算法，运用离散余弦变换对256x256图像进行稀疏处理，完美运行没得任何问题-It is written in my OMP algorithm, the use of the discrete cosine transform 256x256 images sparse, perfect operation did not have any problems
Sparsity-Collaborative-Track
- 基于稀疏表示的目标跟踪,对于稀疏表示应用于图像处理的同志可是一个借鉴。-Robust Object Tracking via Sparsity-based Collaborative Model
SolvePFP
- 图像等运用稀疏表示的方法进行计算识别和分类-Images using sparse representation method to calculate identification and classification
inpaint
- 基于压缩感知的图像修复,，基于图像在复数小波变换上的稀疏性，利用迭代硬阈值方法 求解重构模型，进而获得重构图像.-Based on compressed sensing image restoration, image-based complex wavelet transform on the sparsity of the iterative method for solving hard threshold reconstruction model, and then get the
3-3-1
- 基于图像的稀疏性用OMP算法对图像去噪，思路清晰，容易理解-Based on the sparsity of the image with OMP algorithm for image denoising, clear, easy to understand
SparseRepresentationaItsApplication
- 稀疏表达及其应用的简单介绍，其中涵盖了稀疏表示、特征提取、压缩感知、图像增强、盲源分离、模式分类、目标跟踪和图像超分辨等。PPT和PDF是对应的，并添加了可视化的结果。-Sparse Representation and Its Application: Compressive Sensing, Visual Feature, Image Enhancement, Blind Source Separation, Pattern Classification, Object Tracking a
Blind-motion-deblurring
- 利用稀疏处理单幅图像运动模糊，盲运动图像复原算法。-Sparse handle single image motion blur, blind image restoration algorithm sport。
sr
- 基于稀疏表示来实现图像的目标识别的几种算法-Image based on sparse representation to achieve the objectives identified several algorithms
DCT
- DCT在图像重构，压缩感知以及稀疏表示中的应用-DCT in image reconstruction, compressed sensing and sparse representation of the application
Image-_recon
- 完成两幅图像的稀疏点的匹配和重建，C++的编程环境，opencv函数库-Do two sparse points matching and reconstruction of the image, c++ programming environment, opencv function library