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本源码是基于Markov chain Monte Carlo (MCMC)的Bayesian inference工具包,其中包括MCMC采样，基于MCMC的高斯分类，同时描述了采样的一些方法。其中还有使用文档(toolbox is a collection of Matlab functions for Bayesian inference with Markov chain Monte Carlo (MCMC) methods)

说明：  利用线性规划问题求解稀疏恢复问题的基追踪（basis pursuit，BP）算法，研究了在含有脉冲噪声干扰的原始信号环境下对经典基追踪算法的改进。(basis pursuit (BP) algorithm)

对图片预处理加入高斯噪声，各种经典边缘检测算子对图像进行边缘提取(Gaussian noise on the image pre-processing, a variety of classic edge detection operator to extract image edge)

将Radarsat2极化SAR图像数据转换为散射矩阵及相干矩阵T3的matlab代码,附上的图像文件是用Enviview软件截取转存的各通道实部虚部文件,以及lutsigma.xml查找表文件.作者辛苦所做,希望对SAR初学者有所帮助.(Will Radarsat2 polarization SAR image data is converted to T3 scattering matrix and the coherent matrix of matlab code, the attached image file is transferred Enviview software maintained by the interception of the real part imaginary part of the channel files, and lutsigma.xml lookup table file. Of the hard done, in the hope SAR to help beginners.)

同态滤波器 作用：消除不均匀照度的影响, 增强图象细节。(Filter function with the state: to eliminate the impact of uneven illumination, enhanced image detail.)

This program is able obtain the cemtral point of a template in an image.The program gives 4 output images performing diferent kind of filtering, and giving the center of the matchig template.

SURF的实现代码,用于图像特征提取，对于入门计算机视觉的同学有帮助(SURF implementation code for image feature extraction, for beginners of computer vision students help)

从一张图片中结算其中钢筋数量的图像处理程序(failed to translate)

：数字水印技术作为数字媒体版权保护的有效办法，近年来在国内外引起了人们极大的兴趣。作者采用了DCT离散余弦变换的算法，对图像这种多媒体数字作品进行了数字水印的嵌入和检测研究。并且使用了高效实用的编程工具MATLAB来介绍了一种DCT域的图像数字水印嵌入和提取的(BASIC_WM.M ..........................................cellauto.m ..........................................dctwatermark.m ..........................................detectbasic_wm.m ..........................................plotcorr_coef.m ..........................................wavedetect.m ..........................................wavedetect2.m ..........................................wavemarksvd.m ..........................................wavemarksvd)

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