cloud

基于matlab的高帽变换，能很好地对图像进行一定的处理，实现图像的增强，线性特征的提取，为后续的处理做准备(Matlab-based top-hat transform good image processing, image enhancement, linear feature extraction, to prepare for subsequent processing)

说明：  SIFT特征点的提取和匹配，SIFT算法首先在尺度空间上进行关键点检测，确定关键点的位置和关键点所处的尺度，然后使用关键点邻域梯度的主方向作为该点的方向特征，最后由关键点邻域梯度信息生成关键点的特征向量(SIFT algorithm firstly detects the key points in the scale space, determines the location of the key points and the scale of the key points, then uses the main direction of the key point neighborhood gradient as the direction feature of the point, and finally generates the feature vector of the key points from the key point neighborhood gradient information)

此程序是基于灰度共生矩阵的图像纹理特征提取算法，它进行了四个方向上的灰度共生矩阵的计算，从而得出他们的纹理特征向量，再求均值，使计算进度大幅度提高(This program is based on the GLCM texture feature extraction algorithm, which was four directions GLCM calculation to arrive at their texture feature vector, and then seek means to significantly increase computing progress)

说明：  基于小波变换的数字水印，包含的嵌入与提取代码，原理等(Digital watermarking based on wavelet transform, including embedded and extracted code, principle, etc)

实现航迹融合的算法，多雷达探测实现目标数据的融合并完成对目标的模拟仿真，这里主要是对一个目标的跟踪，需要在vc++6.0上实行(Track fusion algorithms, multi-radar detection to achieve the target data fusion and complete simulation of the target, mainly tracking a target, you need to implement in vc++6.0)

说明：  图像分块处理和计算图像灰度平均值的算法，可用于路面识别预处理(Average value of image block calculation)

matlab 用于图像融合的论文，有各种算法源代码(papers, matlab for image fusion algorithm source code)

利用python和opencv拼接两张图片(Splicing two pictures using Python and opencv)

单目标定很好用的程序，对于单目摄像机的一个标定。张正友博士的方法，对于摄像机标定，切记标定板不能用手机拍摄，因为手机拍摄是变焦的(Single objective of the program is very good, for a single camera calibration. Dr. Zhang Zhengyou s method for camera calibration, remember that the camera calibration board can not be used to shoot the phone, because the phone is to shoot a zoom )

在图像去卷积算法引入先验模型的应用,主要是建立马尔可夫随机场先验模型.很大程度上改进了去卷积的效果,更多的保持了图像的边缘特征.(In image deconvolution algorithm Application of the introduction of a priori model, mainly the establishment of Markov random field a priori model. A large extent, improved the effectiveness of deconvolution, more to maintain the image of the edge feature.)