MRF-ICM

说明：  均值、高斯、中值三种基本的滤波方法与噪声模型(Mean, Gaussian and median filtering methods and noise model)

图象处理用于对BMP格式的图象进行几何校正.(image processing used to BMP format images geometric correction.)

用MATLAB对两幅图片进行图像匹配,程序运用了两种匹配算法:1.sad算法2.ssad算法3.的采用界面输入输出方式.(MATLAB to two picture image matching, and the program using the two matching algorithms: 1. Sad algorithm 2.Ssad algorithm of the input and output interface mode.input/output mode.)

提出一种基于小波变换的图像配准方法。该方法首先用小波变换提取边缘特征点, 同时构成小波金字塔影像。在最高层利 用角度相关系数确定基准图像和配准图像之间的旋转角度, 经多分辨分级搜索匹配得到最终匹配特征点对, 利用这些特征点对待 配准图像进行配准纠正。实验结果表明, 改进方法有较好的效果, 可用于广泛应用领域。(Proposed a wavelet-based image registration method. In this method, using wavelet transform to extract the edge feature points, the same time constitute wavelet pyramid image. Point at the highest level the correlation coefficient using the baseline image registration between image and the angle of rotation, the multi-resolution hierarchical searching and matching features of the final match point, the use of these features point towards registration image registration correction. Experimental results show that the improved method has better results, can be used for wide range of applications.)

利用小波变换进行图像去噪处理，包括各种软硬阈值的选取函数(Using Wavelet Transform for Image Denoising, including a variety of select hard and soft threshold function)

图像处理基本算法其中之一的图像细化(Image processing one of the basic algorithm for image thinning)

hough和randon函数求图像中圆，对于水中气泡检测效果很不错(Circle detection based on random Hough transform)

用Kalman滤波方法对单个目标航迹进行预测，并借助于Matlab仿真工具，对实验的效果进行评估。 (Target tracking application context radar data processing, radar in the search to the goals and objectives of the record location data of the measured target position data (called a point of the track) processing, automatic formation flight path, and the target in the next The moment the position prediction. This article briefly discusses the Kalman filtering method to predict a single target track, and by means of Matlab simulation tools to assess the effect of the experimental.)

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.)

VC6.0环境下使用可视化工具VTK 实现三维重建方法是光线投影法，实现效果较好(3D-reconstruction)