manual_v1.2.pdf

C++，人脸变形，选择图片，在图片中选择一个四边形窗口（人物脸部），然后再在内部选择一个四边形窗口，逆时针选择，然后点击变形直接呈现变形结果，点击动画可以查看人脸变形过程(C++ program, select a picture, choose a quadrilateral window (human faces) in the picture, and then select a quadrilateral inside the window, counter-clockwise to select, then click on the deformation presented directly deformation results, click animated facial deformation process can be viewed)

自己编的利用FreeImage库分割图像的程序,可以将一个图片分成5个不同区域的图片,主要用于壁纸分割.(Own use FreeImage library image segmentation procedure, a picture can be divided into five different regions of the picture, the main partition for wallpaper.)

转换八位256色位图源码，例程程序置入汇编代码，通过图像字节集数据的计算转换为八位256色位图。(Conversion of eight 256-color bitmap source , routine program into assembly code to calculate the conversion by the image data into eight byte set 256-color bitmap .)

SVM算法的线性分类，图像分类单幅遥感图像特征提取分类(Linear classification of SVM algorithm, image classification, feature extraction and classification of single remote sensing image)

2012 CVPR 文章：Segmentation Using Superpixels A Bipartite Graph Partitioning Approach对应的代码(2012 CVPR paper：Segmentation Using Superpixels A Bipartite Graph Partitioning Approach)

AForge.NET-sample

图像去噪，采用GUI界面形式，里面包括高斯滤波，低通滤波和理想滤波三种方法。(Image denoising, using GUI interface form, which includes Gaussian filtering, low-pass filtering and ideal filtering three methods.)

SAR多普勒成像算法matlab实现以及逆合成孔径雷达回波信号成像(Matlab implementation of SAR Doppler imaging algorithm and echo signal imaging of inverse synthetic aperture radar)

奇异值分解波束形成，自适应波束形成仿真。由均匀线阵形式，确定阵列的导向矢量；由阵列导向矢量，对接收信号进行建模仿真；根据约束条件，实现自适应波束形成算法；考察算法性能与信噪比，采样率，观测时间等参数的关系。 (SVD beamforming, adaptive beamforming simulation. Form by the ULA to determine the array steering vector by the array steering vector, the received signal modeling and simulation under constraint conditions, adaptive beamforming algorithm examine algorithm performance and signal to noise ratio, sample rate, observation time, etc. parameters.)

mean shift进行图像分割的matlab代码 非常好用 可直接对灰度或者彩色图像进行分割(matlab code for image segmentation by mean shift)