Harris

输入一组数据，xy值，用来拟合椭圆。只要改变输入数据，该代码就可以直接使用。另附上椭圆拟合算法。(Enter a set of data, xy values, used to fit ellipses. Just change input data, the code can be used directly. Attached on the ellipse fitting algorithm.)

说明：  基于LEE滤波的极化SAR去噪 matlab实现(jiyu lee lvbo jihua SAR matlab)

说明：  调用 envi5.3自带的FMask云检测功能，并输出掩膜文件(Call the FMash cloud detection function of envi5.3 and output the mask file)

说明：  基于hessian矩阵的眼底图像血管增强滤波(Vessel Enhanced Filtering of Eyeground Images Based on Hessian Matrix)

说明：  图像去噪，梯度倒数加权滤波代码噪matlab中实现(Image denoising, countdown weighted gradient noise filtering matlab code to achieve)

视频异常行为检测，可以实现，使用matlab编程(Video abnormal behavior detection can be achieved using matlab programming)

BM3D去噪算法开源代码，不是MATLAB的保密脚本文件，可更改(BM3D,image denoising algorithm)

基于多帧图像插值（Interpolation）技术的方法是SR恢复技术当中最直观 的方法。这类方法首先估计各帧图像之间的相对运动信息，获得HR图像在非均 匀间距采样点上的象素值，接着通过非均匀插值得到HR栅格上的象素值，最后 采用图像恢复技术来去除模糊和降低噪声（运动估计!非均匀插值!去模糊和 噪声）。(In this paper, we propose a novel method for solv- ing single-image super-resolution problems. Given a low-resolution image as input, we recover its high- resolution counterpart using a set of training exam- ples. While this formulation resembles other learning- based methods for super-resolution, our method has been inspired by recent manifold learning methods, par- ticularly locally linear embedding (LLE). Speci?cally, small image patches in the low- and high-resolution images form manifolds with similar local geometry in two distinct feature spaces. As in LLE, local geometry is characterized by how a feature vector correspond- ing to a patch can be reconstructed by its neighbors in the feature space. Besides using the training image pairs to estimate the high-resolution embedding, we also enforce local compatibility and smoothness con- straints between patches in the target high-resolution image through overlapping. Experiments show that our method is very ?exible )

说明：  InSAR数据处理研究，其中采用最小二乘和质量图指导两种相位解缠方法(The research of InSAR Data processing)

基于C++MFC平台进行NDVI计算、最小距离分类、K均值分类，BP神经网络分类等以及精度评价(Based on C++MFC platform, NDVI computing, minimum distance classification, K mean classification, BP neural network classification and accuracy evaluation are carried out.)