object_tracking_based_on_kalman

一篇关于光声成像的图像重建算法研究，开发工具为matlab，罗列了很多理论知识(A photoacoustic imaging of image reconstruction algorithms, development tools matlab, listed a lot of theoretical knowledge )

有关粒子滤波及其改进算法的资料，对初学粒子滤波算法的人很有帮助(Information about particle filter and its improved algorithm, is of great help to beginners of particle filter algorithm )

ncc查询匹配的方法，可以用来做各种图像匹配的简单代码(ncc query matching method can be used for a variety of image matching short code.)

IDL计算影像均值、标准差、偏差指数、信息熵、平均梯度、光谱扭曲程度、相关系数的小程序。(average gradient, correlation coefficient, entropy, cross entropy, joint entropy, mean square error and mutual information, signal to noise ratio, peak signal to noise ratio, )

压缩传感，MATLAB，信号重建，正交匹配追踪，打破乃奎斯特定理(Compressed sensing, MATLAB, signal reconstruction, orthogonal matching pursuit, breaking the Nyquist Theorem)

基于数字图像处理，实现一个车牌分割和识别的仿真系统。要求系统具有界面并实现以下功能： 1）读入交通标志图像； 2）预处理及车牌标志定位； 3）多种图像分割功能； 4）形态学滤波等功能； 5）对标志中的数字进行识别。(Based on digital image processing, segmentation and recognition of a license plate emulation system. Interface and require a system with the following functions: 1) read the traffic sign 2) pre-processing and positioning plate mark 3) a variety of image segmentation functions 4) morphological filtering and other functions 5) to mark the numbers Identification.)

基于多特征描述和DPF区域匹配的图像检索(Based on multi-feature description and matching DPF Regional Image Retrieval)

计算机视觉中，structure from motion的代码(computer vision, structure from motion code)

click energie of image , we can use it to calculate markov field ... and other

基于遗传模拟退火和Otsu法的图像分割。采用一种基于模拟退火算法(SA)的混合遗传算法(GASA),来进行Otsu方法选择阈值，其中进行求解时是非线性的遗传算法（GA）的应用优化了求阈值过程，并尽可能地减少其运算量,而加入SA则避免了遗传算法(GA)常见的早熟收敛现象,从而实现有效简单的图像分割。 (adopt hybrid genetic algorithm(GASA) based on simulated annealing algorithm,choose threshold by Ostu method,which applicated the non-linear genetic algorithm(GA) allows us to optimize the process of threshold. And, where possible, to reduce the computation. in order to achieve effectivly and simply image segmentation. Combination SA is to avoid the common phenomenon about premature convergence in genetic algorithm (GA) to achieve a simple and effective image segmentation.)