Somp

说明：  一篇关于压缩感知的经典文章，压缩感知（Compressed sensing，简称CS，也称为Compressive sampling)理论异于近代奈奎斯特采样定理，它指出：利用随机观测矩阵可以把一个稀疏或可压缩的高维信号投影到低维空间上，然后再利用这些少量的投影通过解一个优化问题就可以以高概率重构原始稀疏信号，并且证明了这样的随机投影包含了原始稀疏信号的足够信息。(A classic article on compressed sensing, compressive sensing (Compressed sensing, referred to as CS, also known as Compressive sampling) different from the modern theory of the Nyquist sampling theorem, which states: the use of a random measurement matrix can be sparse or compressible high-dimensional signal projected to low dimensional space, and then use a small amount of projection by solving an optimization problem to be sparse with high probability to reconstruct the original signal, and prove that random projection of the original sparse signal contains enough information.)

win8压缩解压源码程序，结合易语言多线程支持库，调用API函数实现WIN8系统的压缩解压。(win8 source compression decompression procedures , combined with easy language support for multithreading library , call the API functions WIN8 system of compression and decompression .)

matlab实现的huff图像压缩程序 可成功运行((matlab implementation of huff image compression program which can be run successfully))

利用LZW的压缩算法实现文件的压缩与解压缩。用c++和MFC实现，代码简洁，实现简单，可用(LZW compression algorithm using the file compression and decompression.)

这是LZ77压缩算法的源码，内含使用DEMO(LZ77 compression algorithm This is the source, including the use of DEMO)

二值图像 游程编码 自己测试过。。。绝对可用(Binary image run-length coding themselves tested. . . Definitely can be used)

基于stm32的jpeg图片压缩代码，并且通过串口输出(The stm32-based jpeg image compression code, and output through the serial port)

WinEYS压缩源码例程，程序结合易语言扩展界面支持库，调用API函数实现压缩解压功能。(WinEYS source compression routines, programs combined with easy language support library expansion interface , call the API function to achieve compression and decompression functions.)

简单的压缩感知用于无线传感器的例子，还有贝叶斯压缩感知(Simple compress perception used for wireless sensor examples, and the bayesian compression perception )

CONTOURLET去噪。添加了高斯噪声很好的实现了图像的多尺度分解下的去噪与重建。实现了多尺度分解的子带去噪。(CONTOURLET denoise .this is denoise program. my english is poor!)