chonggou

说明：  SAR-CS成像算法实现，包含运动补偿，速度估计，对0.15m实测数据成过像(SAR-CS imaging algorithms, including motion compensation, the estimated speed of 0.15m measured data into a cross as)

说明：  基于log Gabor小波的相位一致图像纹理特征分析(Based on log Gabor wavelet phase consistent image texture analysis)

基于颜色衰减先验的图像去雾算法源码,作者是Zhu，大家可以作为论文中的比较算法(the matlab code of image dehazing based on color attenuation prior)

这是新提出来的用于图像去噪的非局部均值滤波方法, matlab程序.非常好,你试试.(this is a new proposed image denoising method--non local means filtering, matlab file. you can try!)

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.)

匹配追踪的主程序,用原子与信号内积的方式，对波包进行分解，再进行时频分析(match persuit)

说明：  关于GLSL的点光源，载入模型，纹理。。。。。。。。。。(light engine code OpenGL.)

分割点云，并通过局部拟合求取法向量，实现点云压缩(Split point cloud, and through local fitting strike normal vector of point cloud compression)

用matlab实现了暗通道图像增强，完整源代码，出自暗通道增强算法的提出者。(Dark-channel image enhancement, complete source code from the authors of the dark channel enhancement algorithms.)

经典的4种彩色图像分割方法：CSC.EGBIS.JSEG.Meanshift 的VC++实现；及相关英文文献。绝对值得拥有！哈哈...(The classic four kinds of color image segmentation method: CSC.EGBIS.JSEG.Meanshift of VC++ implementation and the relevant literature in English. Definitely worth having!ha ha ...)