搜索资源列表
cs2235
- 基于轮廓波维纳滤波的图像压缩传感重构论文,利用了轮廓波维纳滤波去噪算子替代迭代阈值法中的阈值算子,进而提出了基于轮廓波维纳滤波的图像压缩传感的重构算法。-Contour-based image compression sensor Povina reconstruction filter paper, using the contour Povina filter denoising operator in the alternative iterative threshold method t
Wavelet_OMP
- 压缩传感,MATLAB,图像重建,正交匹配追踪,打破乃奎斯特定理-Compressed sensing, MATLAB, image reconstruction, orthogonal matching pursuit, breaking the Nyquist Theorem
fen_kuai_Wavelet_OMP
- 压缩传感,MATLAB,图像重建,正交匹配追踪,打破乃奎斯特定理,图像分块处理-Compressed sensing, MATLAB, image reconstruction, orthogonal matching pursuit, breaking the Nyquist theorem, the image block processing
IST
- 可用于降噪,压缩传感等,迭代阈值求解最优解,-Can be used for noise reduction, compression sensing and iterative threshold to solve the optimal solution
l1_ls_matlab
- 一种约束方式,用于降噪和压缩传感等,是稀疏图像的求解最优的方式-A constraint method for noise reduction and compressed sensing, are sparse best way to solve the image
csphantom
- 用于压缩传感重建测试图像,可以任意设置大小尺寸-CSPHANTOM Test image for compressive sensing reconstructions
Block_CS
- 基于分块可压缩传感的图像重建,里面包括contourlet、DWT、DDWT、DCT,图像压缩传感与重建。-Based on the sub-block compressible sensing image reconstruction, which include the Contourlet DWT DDWT,, DCT image compression sensing and reconstruction.
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
Matching-track-CS
- 基于压缩传感的匹配追踪重建算法研究。给出了OMP的一种改进方案。OMP算法本身耗时过长速度过慢,本文的改 进方案将图像进行分块后再处理,从而大大降低了OMP算法每次迭代的矩阵规模。 实验结果表明,该方案在不明显降低重建效果的同时提高了运算速度。-Matching track reconstruction algorithm based on compressed sensing
mp
- 可压缩传感,随机投影,稀疏性,非相干,图像重建-Compressible sensing, random projection, sparse, non-coherent, image reconstruction