image-matching

极化SAR图像处理中，将三个不同极化通道的数据进行为彩色合成的程序(Polarization SAR image processing, will be three different polarization data-channel color composite of the procedures for)

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)

ITK的脑室图像分割,可以对脑部的图像用itk进行分割，用VTK来进行显示。(the segration of brain of ITK )

说明：  最二小乘影像匹配，精度可以达到0.01个像素，也可以最二小乘影像模板匹配。经过修改后可以直接用，只要调用一个函数就搞定，函数参数的说明很清楚，绝对不会有任何困难，非常好用。(Most two Theravada image matching accuracy can reach 0.01 pixel images can also be the most two Theravada template matching. After modifications can be directly used, as long as is you call a function, function parameters, the description is clear and will not have any difficulties, very easy to use.)

于傅里叶变换的图像加密技术研究 具体是将一幅图像用 fft 变换到频域 在频域中进行加密 我考虑的是通过随机相位来加密的方法，请问用matlab怎样实现 加密后在通过 ifft 得到加密后的图象 (Fourier transform in the image encryption technology to study the details of an image is to use fft transformed to the frequency domain in the frequency domain I consider encryption is through random-phase approach to encryption, Will the use of Matlab how to achieve the adoption of encryption ifft be encrypted images)

基于高斯混合模型markov树算法的图像分割。。。(Gaussian mixture model based markov tree algorithm for image segmentation. . .)

该程序实现了harris角点的提取以及其在两幅影像上的配准结果，希望对大家有用(The program implements the harris corner extraction as well as their two images on the registration results, we hope to be useful)

基于HSV与小波包分析的遥感图像融合，首先多光谱图像转换到HSV空间，再与全息图像分别进行小波包分解，然后低频与高频各自采用不同的融合方法，最后得到融合图像。(image fusion)

医学图像配准，医学图像2D_3D配准，基于vc++开发。(The registration of pre-operative volumetric datasets to intra-operative two-dimensional images provides an im- provedway of verifying patient positionandmedical instru- ment location. In applications from orthopedics to neuro- surgery, it has a great value in maintaining up-to-date in- formation about changes due to intervention. We propose a mutual information-based registration algorithm which es- tablishes the proper alignment via a stochastic gradient as- centstrategy. Ourmaincontributionliesinestimatingprob- ability density measures of image intensities with a sparse histogrammingmethodwhichcouldlead to potentialspeed- up over existing registration procedures and deriving the gradient estimates required by the maximization procedure. Experimental results are presented on fluoroscopy and CT datasets of a real skull, and on a CT-derived dataset of a real skull, a plastic skull and a plastic lumbar spine seg- ment.)

本程序实现医学图像的增强，实验显示，处理后的医学图像轮廓清晰，可识性较好。(This procedure to achieve medical image enhancement, experiments showed that the treated medical image outline a clear, identifiable better.)