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Matlab code for CS reocvery

于 2018-01-31 发布文件大小:77KB

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下载积分: 1 下载次数: 4

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代码说明：

压缩感知图形图像图像处理数据恢复代码(Data recovery of compressed sensing image image processing)

文件列表：

Matlab code for CS reocvery, 0 , 2016-12-08
Matlab code for CS reocvery\Demo_CS_BP.m, 9208 , 2010-07-24
Matlab code for CS reocvery\Demo_CS_CoSaMP.m, 3456 , 2010-07-16
Matlab code for CS reocvery\Demo_CS_GBP.m, 8278 , 2010-07-15
Matlab code for CS reocvery\Demo_CS_IHT.m, 2904 , 2010-07-22
Matlab code for CS reocvery\Demo_CS_IRLS.m, 2903 , 2010-07-15
Matlab code for CS reocvery\Demo_CS_LP.m, 11149 , 2010-07-24
Matlab code for CS reocvery\Demo_CS_OMP.m, 3340 , 2010-07-16
Matlab code for CS reocvery\Demo_CS_SP.m, 3434 , 2010-07-15
Matlab code for CS reocvery\Demo_CS_TVeq.m, 12276 , 2010-07-24
Matlab code for CS reocvery\Demo_CS_TVqc.m, 12388 , 2010-07-24
Matlab code for CS reocvery\lena.bmp, 66614 , 2010-05-11

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k-均值聚类算法实现灰度图像分割，输入图像矩阵和聚类中心个数，返回为最终的聚类中心和图像中每个像素所属类的编号（对应于图像矩阵）(k-means clustering algorithm to achieve gray-scale image segmentation, the input image matrix and the number of cluster centers, the return for the final image of the cluster centers and their respective categories in each pixel number (corresponding to the image matrix))

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本设计主要目的是实现染色体的识别计数。首先对图形进行预处理，将图像转化为灰度图、滤波去噪，然后对图像进行二值化，合理选取阈值，进行直方图阈值处理，最后去除图像中面积过小的杂点，最终实现识别计数。(The main purpose of this design is to achieve the identification of chromosome count. The graphical pre-processing, the image is converted to grayscale, filtering denoising, image binarization, reasonable selection of the threshold, histogram thresholding, and finally remove the image area is too small noise , and ultimately identify the count.)

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用lbp实现纹理特征提取，并分类说明: 一共有三个m文件，一个是lbp.m, 存放主要的lbp算法，一个是getmapping,用以做算法的辅助函数，一个是lbptest.m,存放着测试代码。这三个文件需要放到同一个文件夹，并在文件夹中添加相应的图片，具体的图片名字见lbptest.m的代码，运行lbptest.m可以查看结果。代码最后给出效果图这三个文件是最传统的LBP方法，有256种。(With lbp achieve texture feature extraction and classification Description: A total of three m files, one is lbp.m, store the main lbp algorithm, One is getmapping, helper functions for doing arithmetic, One is lbptest.m, kept the test code. These three documents need to put the same folder, and add the appropriate folder, pictures, See lbptest.m specific name of the picture of the code, run lbptest.m can view the results. Finally renderings code These three documents are the most traditional LBP method, there are 256 kinds.)

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