scanning

希尔伯特黄变换方法的安全评估matlab源程序(Hilbert-Huang Transformation security assessment)

基于T熵的多阈值分割,实现了灰度图像的自动转换,以及对灰度图像的二阈值和三阈值的分割算法(T entropy-based multi-threshold segmentation grayscale image automatically converted, and the threshold grayscale images and three threshold segmentation algorithm)

载入一副图像并进行平滑处理与高斯或其他核函数进行卷积有效的减少图像信息内容(Loading an image and smoothed with a Gaussian or other nuclear convolution function effectively reduce the information content of the image)

本程序集合了互信息配准，PV差值，powell算法，基于小波变换的图像融合的一整套算法。只需要在GUI界面输入两幅图像，即可自动完成图像的配准融合。程序包含Matlab源代码。用Matlab打开imagefusion.m，即会弹出gui界面。融合前要输入参考和浮动图像。图像要求像素的 长＊宽 一样。否则会报错。程序只能处理灰度图像，彩色图像也会转化成灰度图像处理。程序代码已经有详细的注释，方便读者理解。(The procedures set of mutual information, PV difference, powell algorithm, based on wavelet transform image fusion set of algorithms. Only need to enter the two images in the GUI interface, you can automatically complete the image registration fusion. Program contains Matlab source code. Using Matlab open imagefusion.m, gui interface will pop up. Fusion before the input reference and floating images. Image requires the same pixel length* width. Otherwise incorrect. Can only handle grayscale images, color images into gray image processing also. Program code has detailed notes, to facilitate understanding.)

基于Canny算子检测图像边缘，其中含有非极大值抑制功能。(Based on Canny operator edge detection image, which contains a non-maxima suppression.)

很好的点云滤波的文章，主要介绍了K-d树的滤波方法(Good point cloud filtering articles, Kd tree filtering method)

双边滤波器，对彩色图像进行处理，效果非常好！(bialteral filter)

文件包含脑部CT图像分割的程序及所用图片(File contains the brain CT image segmentation procedures and images used in)

根据超限像素平滑定义用 Matlab 自编写超限像素平滑法滤波(Super pixel smooth)

1.打开左右两张影像2.Harris算法提取同名点3.显示提取同名点（若要进行下一步匹配则不建议显示，这里只是用于查看是否提取出）4.相关系数匹配（只在找出的同名点内匹配）5.LSM最小二乘匹配（先进行粗匹配，再精匹配）(1 Open the left and right images 2.Harris algorithm to extract two tie points 3 shows the extraction of corresponding points (not recommended to proceed to the next match show, here is used to see if extracted) 4. Correlation coefficient matching (just looking match within a point of the same name) 5.LSM least squares matching (rough first match, then fine match))