SuperResolution

矩形信号的frft（分数傅里叶变换wigner_ville_1.m 单分量信号去噪 wigner_ville_2.m 双分量平行信号去噪 wigner_ville_3.m 3分量信号频率检测）分数傅里叶变换是经典傅里叶变换的另一种改进方式。它的主要特点是提供研究对象从时间域到频率域全过程的综合描述，随着阶数从0连续增长到1，分数傅里叶变换展示出研究对象从纯时间域逐步变化到纯频率域的所有变化特征。因此，分数傅里叶变换提供了远比傅里叶变换多得多的可供选择的数据处理和分析方法。(The rectangular signal FRFT (Fractional Fourier Transform) Score Fourier transform is another modification of the classic Fourier transform. Its main feature is a comprehensive description of the study from the time domain to the frequency domain, with the order of continuous growth from 0 to 1, the fractional Fourier transform demonstrate the object of study from a purely time-domain gradually change to a pure frequency domain variation. Thus, the fractional Fourier transform provides data processing and analysis methods than Fourier transform much more to choose from.)

图形图像处理，混合高斯图像背景估计＆更新(Graphic image processing, mixed-Gaussian background image is estimated )

图像超分辨率重建算法，实现图像的超分辨率重建。(super-resolution code )

按照指定分隔符将已知字符串分割成个部分，并以cell存储(In accordance with the specified separator known string divided into parts, and cell storage)

1.图像去噪MATLAB仿真程序.m 2.图像点扩展函数获取MATLAB仿真程序.m 3.约束最小二乘法图像复原MATLAB仿真程序.m(1.the simulation of denoise. 2.the method to get psf. 3.controlled least squre method to deblur image.)

MATlab图像分割源代码,包含边缘检测，区域分割，直方图(MATlabapplican)

将原图与一幅模板图像进行计算相关 以图像显示相关函数(The original image and a template image to calculate correlation functions related to image display)

移频复调制ZOOMFFT能以指定的、足够高的采样频率分析频率轴上任一窄带内信号的频谱结构，在序列变换点数相同的情况下，ZOOMFFT能获得更高的频率分辨率(The frequency shift the complex modulation ZOOMFFT to specified former spectrum of the signal within a narrow band structure, a sufficiently high sampling frequency analysis of the frequency axis, in the case of the same sequence transform points, ZOOMFFT obtain a higher frequency resolution)

用c++编写的三维图像变换的源代码，也是计算机图像学中经常要学习的一种变换。(Transform the source code written in c++ three-dimensional images, but also often have to learn a transformation in the computer iconography.)

使用cnn + svm的分类，结果运行不错(Using CNN + SVM classification, the result runs pretty well.)