Based-on-

beta过程+稀疏表示，做单帧超分辨率重建(single imagle super-resolution by beta process)

采用8个阵元，利用CAPON算法，进行DOA，画出波达方向估计误差随着信噪比变化的曲线图(Eight elements, the use of the CAPON algorithm of DOA draw the DOA estimation error changes with the SNR curve)

VC和MATLAB混合编程实现快速傅立叶变换(VC and MATLAB programming Fast Fourier Transform Mixed)

迭代最佳阈值分割算法，寻找最佳阀值检测边缘(best iteration threshold segmentation algorithm to find the best edge detection threshold)

任意航迹下单块的基于相位历史域的波前弯曲补偿算法(Single block of arbitrary Track bending compensation algorithm based on wavefront phase history domain)

基于OpenCV实现的图像切割程序，通过程序中参数设置分块的数量和大小(The project is uesd to break an image into block)

harris, harris-laplace方法，特征点检测方法总结(harris, harris-laplace method, Feature Point Detection Methods)

matlab实现图像的读取，灰度变换、二值化、边缘检测和hough变换，包含有简单界面。(matlab image read, gray-scale transformation, binarization, edge detection and hough transform, contains a simple interface.)

背景减除的完整算法，《A Statistical Approach for Real-time Robust Background Subtraction and Shadow Detection》作者源代码(The "src" folder contains all of the source code. To run the program, follow these simple steps: 1. Start MATLAB and ensure the "src" folder is your current working directory. 2. Edit "bs.m" and "classify.m" so that the file paths point to the proper directories as specified. 3. In the MATLAB environment type "bs" which will train the background model from the sequence you specified in (2). 4. In the MATLAB environment type "classify" which will classify the sequence of images you specified in (2). 5. Now the classified images should be saved to disk in the folder you specified in (2).)

实现了一个基于颜色、纹理、形状综合特征的MatlabGUI图像检索系统。(Bulit an image retrieval system based on which combines these three features and realizes user-defined weights.)