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bcs-spl-1.3-1.tar
- 分块压缩感知中稀疏表示增加方向性提高重构质量-Block compression to increase directional to improve the reconstruction quality perception in sparse
CS_recovery_algorithms_OMP_SP_IHT
- 基于Matlab编写压缩感知重建算法集，包括OMP，CoSaMP，IHT，IRLS，GBP，SP和ROMP.-Matlab codes for CS recovery algorithms, including OMP, CoSaMP, IHT, IRLS, GBP, SP and ROMP.
BCS
- 压缩传感是一个从2006年左右开始兴起的研究领域，它关注于如何采样信号，也就是信号的采样方式或者压缩方式。通过设计一种特殊的采样方案，可以使得采样频率降低为信号的“信息率”，而不是传统的奈奎斯特采样率，于是，实际的采样率可以大大低于奈奎斯特频率，却只损失很少的信息量，依然保持了充足的信息量足以恢复出采样前的原始信号。这个研究思想挑战了奈奎斯特频率的理论极限，会对整个信号处理领域产生极其深远的影响，同时，信号处理的许多应用领域也会随之发生根本性的发展和变化。 -Compressive sens
Cyclic(73)
- 循环码的定义以及由生成多项式求解生成 矩阵和系统生成矩阵的过程，并在Matlab环境下写出了循 环码的编码器和解码器代码，实现了编码和译码功能。分析和讨论了 此码发现错误、纠正错误的能力，并讨论了其与线性分组码、Hamming 码等信道编码的区别与联系。 - Definition of cyclic codes generated by the polynomial generator matrix of the process of seeking system, writte
ms-bcs-spl-1.2-2
- matlab code for image compressive sensing. block compressive sensing is used.
BCS-SPL-1.5-new
- Block-based random image sampling is coupled with a projectiondriven compressed-sensing recovery that encourages sparsity in the domain of directional transforms simultaneously with a smooth reconstructed image. Both contourlets as well as comp
bcs-spl-1.5-1
- Block Compressed Sensing of Images Using Directional Transforms
mc-bcs-spl-1.0-1
- Multiscale Block Compressed Sensing with Smoothed Projected Landweber Reconstruction
bcs-spl-1.5-1.tar
- 一种适用于图像的压缩感知采样策略和重建算法，采样策略是基于块的图像稀疏采样矩阵，重建算法为smoothed projected Landweber（SPL）迭代算法。-BCS-SPL combines block-based compressed-sensing sampling (BCS) of an image with a smoothed projected-Landweber (SPL) iterative reconstruction. Sampling is driven by r
BCS-SPL-1.5-1
- These MATLAB programs implement the Block Compressed Sensing - Smoothed Projected Landweber (BCS-SPL) algorithm as described in paper: S. Mun and J. E. Fowler, "Block Compressed Sensing of Images Using Directional Transforms," submitted to
BCS-FOCUSS
- Matlab program for Block Compressive sensing using FOCUSS
bcs-spl-1.5-1 (1).tar
- BCS-SPL将图像的基于块的压缩感测采样（BCS）与平滑的投影Landweber（SPL）迭代重建相结合。采样是通过逐块应用随机矩阵来驱动的，而重建则是预期的Landweber（PL）重建（也称为迭代硬阈值（IHT））的变体，其结合平滑操作（维纳滤波）减少块效应。实质上，除了PL所固有的稀疏性之外，这种滤波操作还能提供平滑性。(BCS-SPL combines block-based compressed-sensing sampling (BCS) of an image with a sm