youxianchafenfa

MATLAB coding for 8 QAM is given

用matlab，编写直接线性变换的程序，解算11个参数和内外方位元素(With matlab, write direct linear transformation program solver 11 parameters and internal and external orientation elements)

免疫算法中的克隆选择算法，运用该算法能够进行故障诊断。运行之后效果较好。(Immune algorithm in the clone selection algorithm, using the algorithm capable of fault diagnosis. Running after the effect is good.)

这三个小程序都是matlab的.m文件，分别实现用灰度变换的方法增强图像的对比度和直方图均匀化，模拟图像受高斯白噪声和椒盐噪声的影响。(The three procedures are Matlab. M documents, were used to achieve gray transform method to enhance the contrast of the image and histogram equalization. Simulation images by white Gaussian noise and the noise of Salt and Pepper.)

matlab simuink 模糊控制器tank 改进(matlab simuink improved fuzzy controller tank)

最小二乘回归分析算法，进行逐步线性回归，实现了图像的加水印，去噪，加噪声等功能。( Least-squares regression analysis algorithm, Stepwise linear regression, Realize image watermarking, de-noising, plus noise and other functions.)

Block Matching Algorithms for Motion Estimation This project contains the project report and source code by Aroh Barjatya for Digital Image Processing Class at Utah State University. Following is a short description of the m files in this zip motionsEstAnalysis.m Script to execute all Algorithms motionEstES.m Exhaustive Search Algorithm motionEstTSS.m Three Step Search Algorithm motionEstNTSS.m New Three Step Search Algorithm motionEstSESTSS.m Simple And Efficient Search Algorithm motionEst4SS.m Four Step Search Algorithm motionEstDS.m Diamond Search Algorithm motionEstARPSm Adaptive Root Pattern Search Algorithm costFuncMAD.m Mean Absolute Difference Function minCost.m minimum cost among macro blocks motionComp.m motion compensated image creator imgPSNR.m finds image PSNR w.r.t. reference image The test images can be found at http://cc.usu.edu/~arohb/caltrain.zip

the configuration files for both the uplink and downlink of lte

能够实现Sparse Coding，对IMAGES.mat文件进行训练。(To achieve Sparse Coding, carries on the training to the IMAGES.mat file)

This project is on type of techniques used to enhance an image, detection of edges. In this project we have used neighborhood processing for the edge detection using convolution mask. And to increase the contrast of an image, we stretched each component of an rgb image.