attack

通过使用块匹配法实现运动矢量的检测，块大小和搜索区域大小可自定(Achieved through the use of block matching motion vector detection, block size and search area size can be customized)

品质因子可调的离散小波变换工具箱，可通过参数灵活控制小波函数的频域窗宽(Discrete wavelet transform toolbox with quality factor adjustable, flexible control parameters through the wavelet function in the frequency domain window width)

天津工业大学课程设计，内容包含vs2010对图像的灰度化，二值化，边缘检测。包含单纯c语言编写的对图像的灰度化，二值化，边缘检测的一个.C文件，可以直接用vc6.0运行，也可以直接在DSP上运行，还包含一份详细的设计报告。(Tianjin Polytechnic University curriculum design, content includes vs2010 grayscale image binarization, edge detection. Contains pure c language for image graying, binarization, edge detection is one. C file that can be run with vc6.0 can also be run directly on a DSP, also contains a detailed design report.)

主动轮廓模型图像分割算法，讲XU改进的算法用MATLAB进行实现(Active Contour Model for Image Segmentation Algorithm, speaking XU improved algorithm using MATLAB for the realization of)

对已有图像进行锐化，这里有不同的方法对比，效果非常好，非常显著(The existing image sharpening, there are different methods to contrast, effect is very good, is very significant )

说明：  布谷鸟搜索（Cuckoo Search，缩写 CS），也叫杜鹃搜索，是由剑桥大学杨新社（音译自：Xin-She Yang）教授和S.戴布（S.Deb）于2009年提出的一种新兴启发算法。(Cuckoo search, also known as cuckoo search, is a new heuristic algorithm proposed by Professor Xin She Yang of Cambridge University and S. DEB in 2009.)

在matlab的基础上，使用掩膜图像分割出上层图像(On the basis of matlab, mask image is used to segment the upper image)

说明：  curvelet变换贝叶斯估计方法，用于估计含噪声图像的噪声参数。再对图像进行去噪处理(curvelet transform Bayesian estimation methods used to estimate the image noise with noise parameters. Re-image de-noising processing)

k均值聚类，类数可以自行指定，输出散点图，红色十字为聚类中心(K-means clustering, the class number can be specified on its own, the output scatterplot chart, and the Red Cross for clustering center)

这个Matlab程序，可以从.OBJ文件中读取三维模型，并转换成单元体表示。同时提供了一个绘图plot函数，来可视化三维物体。 (The Matlab program can be. OBJ file to read three-dimensional model, and converted into cell precursors express. At the same time provides a mapping function plot to visualization of three-dimensional objects.)