yasuobi

说明：  输出带连接点的匹配影像，基于opencv(Output matched image with connection points, based on OpenCV)

计算指纹方向场的代码。。。。。。。。。。。。(code for computing orientation of fingerprint )

K均值聚类算法对图像进行分割，实验用程序，亲测可用。(K-means clustering algorithm for image segmentation, experimental procedures, pro-test is available.)

将meanshift算法思想融入harris角点检测算法中，通过设置门限终止迭代漂移，亚像素级别地进行角点检测。(The mean shift algorithm ideas into a corner detection algorithm, terminate the iteration drift, carried out by the sub-pixel level corner detection limit by setting the door.)

RAT，即Radar Tools，用IDL语言开发的雷达图像处理软件(v0.21新版本)，内含所有源代码。亲，学习雷达的、图像处理的、IDL的都可以学习一下哦！(RAT, namely Radar Tools, using IDL language development of the radar image processing software ( v0.21 version ), containing all the source code.Pro, learning radar, image processing, IDL can learn about oh!)

Image processing of band reject filter and archive particular bit of an 8 bit pixel of an image

说明：  使用lbp算法来计算出一副图片的纹理程度，归一化处理(LBP calculates the texture level of the image)

在信号与系统中，用希尔伯特变换对最小相位信号的实部和虚部进行相互变换，同时包含连续时间傅里叶变换(CTFT),反连续时间傅里叶变换（ICTFT），离散时间傅里叶变换（DTFT），反离散时间傅里叶变换（IDTFT）的程序(In signal and system, transform the real and imaginary part of the signal with minimum phase using Hilbert Transform. CTFT,ICTFT,DTFT and IDTFT are also included.)

非常适合计算机视觉方面的研究使用,包括四元数的各种计算,算法优化非常好，几乎没有循环。( Very suitable for the study using computer vision, Including quaternion various calculations, Algorithm optimization is very good, almost no circulation.)

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 )