one-based

读取一24位彩色图像，计算其以下图像特征： 1）灰度直方图 2）颜色直方图（RGB3个通道） 3）方向梯度直方图（HOG，将图像分成4*4 16个块，8个梯度方向） (Read a 24-bit color images, calculate the following image features: 1) Histogram 2) color histogram (RGB3 channels) 3) histogram of oriented gradients (HOG, the image is divided into 4* 4 16 blocks, 8 gradient directions))

图形处理的部分，能进行图像的中值过滤处理(To the median filter for image processing)

源点定位程序，可用于检测连通域等功能，代码是c/c++的，放心使用。(Source point positioning procedures, can be used to detect other functions connected domain, the code is c/c++, and ease of use.)

bgslibrary_x86_v1.9.2,是MFC的实现文件，包含37种背景减除算法，对于做目标提取的研究非常有用。(The BGSLibrary was developed by Andrews Sobral and provides an easy-to-use C++ framework based on OpenCV to perform background subtraction (BGS) in videos. )

合成孔径雷达目标的特征提取及其识别技术。国防科大写的！(synthetic aperture radar target feature extraction and recognition technology. Written by which this university!)

源码包括了常用的图像处理方法，代码详细，适合初学者(Source code, including the commonly used image processing method, the code in detail, suitable for beginners)

裁剪以RGB565格式保存的BMP文件，涉及位图掩码内容(imagecut of the BMP picture which saved with RGB565 format and mask)

实现图像的锐化浮雕等效果。当然，这是我自己弄了很多次之后的。我也忘了它实现的是什么效果了，反正就是大概图片处理一类的。(To achieve the effect of image sharpening and other relief. Of course, I get many times. I also forget to realize what effect, anyway, is about image processing class.)

C语言实现bmp图像放大缩小，24位bmp图像(The C language bmp image zoom, 24 bmp image)

三维激光点云配准是点云三维建模的关键问题之一。经典的 ICP 算法对点云初始位置要求较高且配准 效率较低，提出了一种改进的 ICP 点云配准算法。该算法首先利用主成分分析法实现点云的初始配准，获得较好 的点云初始位置，然后在经典 ICP 算法的基础上，采用 k － d tree 结构实现加速搜索，并利用方向向量夹角阈值去除 错误点对，提高算法的效率。实验表明，本算法流程在保证配准精度的前提下，显著提高了配准效率。 (Three-dimensional laser point cloud registration is one of the key three-dimensional point cloud model. High classical ICP algorithm to the initial position of the point cloud registration requirements and low efficiency, proposed an improved ICP point cloud registration algorithm. Firstly, the use of principal component analysis of the initial point cloud registration, get a better initial position of the point cloud, then the basis of classical ICP algorithm using k- d tree structure to achieve speed up the search, and using the direction vector angle the removal of the threshold point error and improve the efficiency of the algorithm. Experiments show that the algorithm processes to ensure the accuracy of registration under the premise, significantly improve the efficiency of registration.)