HoughMFC

基于OpenCV实现的图像切割程序，通过程序中参数设置分块的数量和大小(The project is uesd to break an image into block)

this is a project about animation. how do we form the shape to make it look like car, house abd so on. with the colours that wee like and the movement.

图像处理的KMP算法源程序，KMP算法是一种基本的、实用的字符串比较算法，广泛应用于图像处理和模式识别。(Image processing algorithms source KMP, KMP algorithm is a basic, practical string comparison algorithm, widely used in image processing and pattern recognition.)

说明：  在VC中实现了使用Moravec算子对遥感影像进行特征点的提取，缺点是速度较慢。不过提取效果不错！(Implemented in VC using Moravec operator of remote sensing images feature point extraction, the disadvantage is slow. However, extracting good results!)

针对图像秘密共享前需要像素置乱的问题，基于(t, n)门限多重秘密共享思想，提出一种免置乱的图像秘密共享方案，以第n+1人的秘密份额作为因子参与秘密分割与重构，加大相邻像素之间的差距(Based on (t, n) threshold multiple secret sharing ideas, and put forward a kind of scrambling image from secret sharing scheme to n+ 1 people share the secret as factors involved in secret segmentation and reconstruction, increase the gap between adjacent pixels)

SAR成像算法的分析； SAR成傢算法简要介绍 ；Chirp-scaling算法 ； 分布式小卫星SAR解方位多普勒模糊的点目标仿真； 分布式小卫星SAR成像的仿真参数 ； 点目标成像仿真及结果 (SAR imaging algorithm analysis SAR algorithm married briefly Chirp-scaling algorithm distributed small satellite SAR azimuth Doppler ambiguity solution point target simulation distributed small satellite SAR imaging simulation parameters Point Target Imaging Simulation and results)

opencv c++将彩色图像转换为灰度图像进行边缘检测，(opencv c++ to convert color images to gray-scale image edge detection,)

微波遥感集中实习SAR影像几何校正，微波遥感几何校正(geometric correction of SAR)

说明：  基于Kmeans算法的图像分割，一般Kmeans是数据挖掘中用来聚类的，本试验利用图像中的灰度值作为Kmeans算法的原始点，进行图像分割(Kmeans algorithm based on image segmentation, data mining in general Kmeans is used to clustering, the trial use of the image gray value as the original algorithm Kmeans spots for Image Segmentation)

本代码实现的功能：24位位图（BMP）的灰度化。具体实现过程：打开图像文件,找到数据区(每3个字节代表一个象素的R,G,B值),循环扫描,根据RGB的权重,计算出灰度值. 如果要得到256色灰度图,则要新建一个调色板,修改信息头和文件头.(Realize the function of the code: 24-bit bitmap (BMP) of the gray. Concrete realization of the process: Open the image file, locate the data area (3 bytes per pixel on behalf of a R, G, B values), cyclic scan, according to the weight of RGB, gray value is calculated. If you want to get 256 colors grayscale, would create a new palette, modify the header and file header information.)