摄影测量点云 Grid

根据D. Comaniciu, P. Meer: Mean Shift: A robust approach toward feature space analysis 以及 C. Christoudias, B. Georgescu, P. Meer: Synergism in low level vision.这两篇文献提供的方法编写的图像分割代码，作者是 Chris M. Christoudias, Bogdan Georgescu，代码经我看了后加了丰富的中文注释，希望可以给各位带来阅读上的方便。 基于meanshift的聚类分割方法包括滤波、区域融合等操作，通过调整sigma和sigmar来调整分割效果。(According to D. Comaniciu, P. Meer: Mean Shift: A robust approach toward feature space analysis, and C. Christoudias, B. Georgescu, P. Meer: Synergism in low level vision. These two documents prepared by the methods provided by image segmentation code , the author is Chris M. Christoudias, Bogdan Georgescu, after I read the code, add a rich Chinese notes, hoping to bring you the convenience of reading. Segmentation method based on clustering meanshift including filtering, regional integration and other operations, and by adjusting the sigma sigmar to adjust segmentation results.)

椭圆、圆、矩形等的识别，在MATLAB下运行.(Ellipse, round, rectangle recognition.)

FDK重建算法 希望对其他人能有帮助 用C和cuda 实现的(fdk reconstrcution algorithm using cuda and c source code hope to help others it may be usefull. it is implented by c and cuda)

通过统计直方图并作相应的处理完成了红外图像非均匀性校正，特别是针对红外图像中常见的条纹非均匀性(Through statistical histogram and processed accordingly infrared image non-uniformity correction, especially for the common striped infrared image non-uniformity)

计算图像的多重分形谱。它是分形的多尺度衡量的分型参数。(Calculated images multifractal spectrum. It is a multi-fractal measure the sub-type parameters.)

基于MeanShift算法将图像进行平滑处理去噪并分割(MeanShift algorithm based on smoothing the image de-noising and segmentation)

目标跟踪，使用基于颜色特征的粒子滤波跟踪算法。使用方便，较精确的实现目标跟踪功能(Target tracking using particle filter based on color feature tracking algorithm. Easy to use, more accurate tracking goals)

包含二维曲波变换、反变换；三维曲波变换；二维曲波变换(Including two-dimensional Qu Bo transform, inverse transform, 3D Qu Bo transform, and two-dimensional Qu Bo transform)

利用contourlet变换、小波变换等方法，进行图像去噪，经过调试，完全可以运行，效果不错(Contourlet transform, wavelet transform methods for image denoising, debugging, can run, good results)

说明：  PWLS算法主要用于CT重建前的投影数据处理，能够很好的用于CT迭代算法中，对图像进行去噪(PWLS algorithm is mainly used for projection data processing before CT reconstruction. It can be well used in CT iterative algorithm to denoise images.)