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基于小波变换的利用阈值法迭代法的图像分割技术(Wavelet Segmentation of the iteration method)

比较反滤波和维纳滤波对一幅图像复原的效果。从两方面出发，一是对运动模糊和均值模糊复原的能力，二是抗噪能力，各种情况分别都进行了对比(Comparison of inverse filtering and Wiener filtering on an image restoration results. Proceed in two ways, first on the motion blur and the mean fuzzy recovery capability and noise immunity, all cases are compared separately)

说明：  实现了图像的打开功能，并能实现图像打开时的扫描，渐进，马赛克等功能(To realize the image of the open function, and can achieve image scans open, progressive, mosaic and other functions)

多样性密度算法,EM-DD算法,最好的多示例学习算法之一,MATLAB实现.(Diverse density algorithm, EM-DD algorithm, one of the best multi-instance learning algorithm, MATLAB.)

实验证明，本方案对于帧间位移较为明显的单个平移运动刚体，特别是外部轮廓较为平滑的物体具有良好的分割与跟踪效果。(experiment proved that the program for the inter-frame displacement is quite obvious that the single translation rigid movement, particularly smooth external contours of objects more good segmentation and tracking results.)

matlab结合GPU的资料，初学者可以看看，很不错的解释,适合参考(matlab GPU combined data, beginners can see, very good explanation for the reference)

矩形检测：用霍夫直线检测方法来对图像中的矩形进行检测。开发环境：vc6，需要安装OpenCV。OpenCV只是用来读取和显示图像等简单操作。(Rectangle detection: Hough line detection method using the image of the rectangle to test. Development Environment: vc6, need to install OpenCV. OpenCV is used to read and display images such as simple operation.)

基于规格化Hough变换的天波超视距雷达检测前跟踪算法(Hough transform based on the normalized horizon radar detection and tracking algorithms)

基于retinex理论的图象增强处理，一种新型的算法，效果挺好(Based on the Retinex theory of image enhancement processing, a new type of algorithm, the effect of good)

内含张正友，tsai的标定方法，可以求解摄像机内参数u轴尺度因子，v轴尺度因子，摄像机外参数：两摄像机坐标系原点之间的旋转矩阵和评议矩阵，可以得出摄像机像素参数，焦距，畸变系数，并且带有优化结果。(Containing Zhang Zhengyou, tsai calibration method that can solve the camera parameters u-axis scale factor v The axis scale factor, the camera extrinsic parameters: the rotation matrix between the two camera coordinate origin, and appraisal matrix can be drawn from the camera pixel parameters, focal length distortion coefficient, and with optimal results. )