SARmovingtarget

颜色特征提取，颜色直方图，为matlab 源文件(feature extraction,colorhist,matlab)

高斯粗糙表面的散射系数，输入参数含波长，需要regeng.m产生高斯粗糙表面。(rs1dg computes the bistatic scattering coefficient for Gaussian rough surfaces with Gaussian spectrum.)

sar图像处理中的双阈值分割算法的matlab实现代码(Double threshold segmentation algorithm of SAR image processing of matlab code )

通过Markov随机场（MRF）实现图像的分割，例程给出了图像分割为3类的MRF算法(By Markov random field (MRF) for image segmentation, image segmentation routine gives the MRF algorithm for the three classes)

说明：  光流计算得到运动场。使用算法为Lucas Kanade算法。(optical flow calculated Sports Ground. Lucas uses algorithms to Kanade algorithm.)

粒子滤波去噪程序 目标跟踪 粒子滤波的实验程序( particlefilter target tracking)

合成孔径雷达图像目标检测资料，很有用的哦(Target detection in correlated SAR clutter)

说明：  基于区域的分裂合并图像分割方法，包含三个m文件，predicate是分裂合并准则代码，split_test用于检测是否需要分裂，splitmerge用于分裂合并(Region Based Split Merge image segmentation method, including three m files, predict is the splitting and merging rule code, split_ Test is used to detect whether splitting is needed, and splitmerge is used for splitting and merging)

來自於2012年IEEE TIP的論文 Efficient Contrast Enhancement Using Adaptive Gamma Correction With Weighting Distribution ，其功能為透過分析影像中的直方圖統計資訊，達到快速增強影像對比的結果。(From the 2012 IEEE TIP paper "Efficient Contrast Enhancement Using Adaptive Gamma Correction With Weighting Distribution"which functions as a histogram of the image by analyzing statistical information, to quickly enhance image contrast.)

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.)