zishiyinglvbo

一种简单高效地基于压缩感知的跟踪算法。首先利用符合压缩感知RIP条件的随机感知矩对多尺度图像特征进行降维，然后在降维后的特征上采用简单的朴素贝叶斯分类器进行分类。该跟踪算法非常简单，但是实验结果很鲁棒，速度大概能到达40帧/秒(A simple and efficient tracking algorithm based on compressed sensing. Firstly, with the random sensing matrix compressed sensing RIP conditions for multi-scale image feature dimension reduction, and then use the naive Bias classifier simple classification in the feature reduction after the. The tracking algorithm is very simple, but the results are robust, speed can reach 40 frames per second)

常用的图像去噪算法，基于隐马尔可夫树模型的小波去噪 基于尺度空间和context模型相结合的自适应小波去噪 基于尺度和空间混合模型的小波图像去噪 Bayes估计阈值软门限去噪 (The denoising algorithm used in image denoising, wavelet hidden Markov tree model based on adaptive wavelet denoising combining the scale space and context model based on wavelet denoising image scale and spatial mixed model based on Bayes estimation soft threshold denoising )

数字识别PCA方法，对其它图像同样适用，程序简便。(Digital identification PCA method, on the other images of the same application, the program is simple.)

对BMP文件进行图像处理，包括：边缘检测、频域变换、几何变换、图像变换校正、灰度变换、图像编码、平滑和匹配(BMP files for image processing, comprising: an edge detection, a frequency domain transformation, geometric transformation, image transformation correction gradation conversion, image coding, and matching the smooth)

本程序实现图像LENA的压缩传感 程序作者：沙威，香港大学电气电子工程学系，wsha@eee.hku.hk(The procedure of image compression sensing process by LENA: Javert, University of Hong Kong Electrical and Electronic Engineering, wsha@eee.hku.hk)

水平集图像分割代码，对应论文为Li C, Xu C, Gui C, et al. Level set evolution without re-initialization: a new variational formulation[C]//Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on. IEEE, 2005, 1: 430-436.(Level set image segmentation code, the corresponding papers of Li C, Xu C, Gui C, et al Level set evolution without re-initialization:.. A new variational formulation [C]// Computer Vision and Pattern Recognition, 2005 CVPR 2005 IEEE. Computer Society Conference on IEEE, 2005, 1:. 430-436.)

image processing and image statistics

人体脑图像分割技术研究a. 对原始的二维医学图像进行滤波，封装成三维体数据。 b. 采用合适的多阈值分割方法得到合适的双阈值，对三维体数据进行二值处理，得到分割出的三维人脑图像。 c. 对得到的三维人脑二值图像进行数学形态学操作，并利用种子填充进行区域修整，得到较好的三维人脑分割结果，并给以三维显示。 (err)

利用matlab对多光谱遥感影像进行水体指数（ndwi）以及植被指数（ndvi）提取(Extraction of Water body Index (ndwi) and vegetation Index (ndvi) from Multispectral remote Sensing Images by matlab)

自己写的Normalized Cut图像分割，聚类程序，程序非常清晰，花了很长时间调试。(Normalize Cut)