Diverse-Density

Fast_and_Robust_Multi-Frame_Super-Resolution这篇文章的算法实现。内含BTV算法和改进的btv算法实现超分辨率重建。(This article Fast_and_Robust_Multi-Frame_Super-Resolution algorithm. Containing BTV algorithm and improved the btv algorithm to achieve super-resolution reconstruction.)

Calculate the Laplacian of an image, can be accelerated by the GPU.

KRUSAL算法实现最小生成数的 最小生成数的 最小生成数的(The KRUSAL algorithm realizes the minimum generating number of the minimum generating numbe)

MKL多核学习综述文章对应的很多MKL代码的合集，里面有很多有代表性的代码，非常详细！(MKL multicore learn many review articles MKL code corresponding collection, there are a lot of representative code, very detailed!)

说明：  小波分析增强滤波。小波变换的原理类似傅里叶变换，只是把三角函数基换成了小波基。与傅里叶变换不同，小波变换有两个变量：scale和translation。scale控制小波函数的收缩，其导数即为频率，translation控制小标函数的平移，平移量对应时间。通过信号的伸缩平移，可以得到某种重合情况，这样积分也会得到一个极大值，不同的是，得到频率成分的同时，还可以知道该频率的时间位置。(Wavelet analysis enhances filtering.The wavelet transform works like the Fourier transform, except that the trigonometric basis is replaced by a wavelet basis. Unlike the Fourier transform, the wavelet transform has two variables: scale and Translation. Scale controls the contraction of the wavelet function, its derivative is frequency, translation controls the translation of the small scale function, and the translation corresponds to the time. By stretching and shifting the signal, you can get some kind of coincidence, so that the integral will also get a maximum, but the difference is that when you get the frequency component, you can also know the time position of that frequency.)

matlab OTSU 简易的大津算法 求最佳阈值的。(matlab simple algorithm seeking Otsu threshold.)

基于深度图的图像修复，有完整的代码和实验图像。(Image restoration based on the depth chart, there is a complete code and experimental images.)

Visual Tracking via Locality Sensitive Histograms.基于局部敏感直方图的目标跟踪算法，该算法在CVPR2013中出现，算法较简单但却非常有效，值得各位研究视觉跟踪算法的同行研究(Visual Tracking via Locality Sensitive Histograms)

压缩感知CS——采用小波变换进行稀疏表示，高斯随机矩阵为观测矩阵，重构算法为OMP算法，对256*256的lena图处理，比较原图和OMP算法在不同采样比例(0.74、0.5、0.3)下的重构效果，并各运行50次，比较算法性能PSNR和每次的运行时间 (Compressed sensing CS- using wavelet transform as sparse representation, Gaussian random matrix as the observation matrix and OMP algorithm as the reconstruction algorithm. Compare lena figure and the reconstruction results using OMP algorithm at different sampling ratio (0.74,0.50.3),then each runs 50 times, compare the performance of PSNR and each running time)

基于稀疏字典和稀疏编码的图像去噪算法，基于低秩约束的高光谱条纹噪声去除，包含论文及代码(Based on sparse dictionary and sparse coding image denoising algorithm, based on low rank constraints of hyperspectral fringe noise removal, including papers and code)