video-processing-

本文针对多光谱图像配准中不同光谱图像间存在较大的灰度差异、同一景物在不同波段表现的特征也各不相同等问题，提出了基于互信息相似性测度的多光谱图像配准算法。(In this paper, multi-spectral image registration between different spectral image there is a big difference in gray scale, the same scene in different bands performance characteristics are different questions, we present a similarity measure based on mutual information of multi-spectral image registration algorithm .)

MATLAB 计算医学图像的配准，融合 基于SIFT方法的配准()

本文介绍了一种 )’’ 多系统静态基线数据处理方法!该方法使用统一的方式来处理 &’ 5.)6’’ 北斗 及三者融合的观测数据#这种处理方法已经实现在广州南方测绘仪器有限公司的静态后处理软件中#本文使用实际数据验 证了这种处理方法!得到了较好的结果(This article describes a ) ' multi-system static baseline data processing method! This method uses a unified way to deal & ' ' 5.) 6' ' ' Compass and three observational data fusion# This treatment method It has been achieved in the static Guangzhou South mapping Instrument Co.# post-processing software used herein, the actual data validation of this approach! Get better results)

说明：  opencv入门程序，使用opencv模式读取图像并显示，在vs环境下调用matlab进行图像读取和显示(opencv entry procedures, read the image using opencv mode and display, in the vs environment, call matlab to read and display the image)

C++和halcon结合，用于图形处理时进行三相机标定(C++ and halcon combined for three camera calibration)

第8章 图象的检测及模板匹配 图象的分割与检测(识别)实际上是一项非常困难的工作。很难说清楚为什么图象应该分割成这样而不是那样。(Chapter 8 Detection of image template matching and image segmentation and detection (recognition) is actually a very difficult task. It is hard to say clearly why the image should be divided into such and not as.)

包含基于VC++的各种图像、视频处理的源码如图像增强、灰度位图处理、图像平移旋转、bmp2txt等程序源码(Contains various images VC++ based video processing source code, such as image enhancement, grayscale bitmap processing, image translation and rotation, bmp2txt program source code, etc.)

用于图像拼接的素材，可用于全景图拼接。主要是JPG形式，可通过SIFT算法进行处理(Material for image stitching, can be used for panorama stitching. Mainly JPG format, can be handled by the SIFT)

说明：  对图像进行中值滤波，去除噪声，并与原图像进行比较(Median filter on the image to remove noise, compared with the original 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.)