spiht_5

说明：  粒子滤波器matlab实现，用于实现目标检测算法(Particle filter matlab realized, for the achievement of Target Detection Algorithm)

houph变换，通过梯度函数得到图像的梯度矩阵，通过检测圆检测眼睛位置。(houph transform, through the gradient function to be the image gradient matrix, circle detection by detecting the location of the eyes.)

基于matlab平台的fft加窗插值算法，适用于信号分析(Wft window interpolation algorithm based on matlab platform, suitable for signal analysis)

计算波导的matlab程序，主要是传输矩阵方法(Waveguide matlab calculation programs)

目前MATLAB里边对于多点计算仿射矩阵普遍采用RANSAC法，但是比较麻烦计算量也相对较大，通过最小二乘法来进行仿射矩阵的估计能够大大提高该效率，所以奉上自己在实验室写的仿射矩阵估计函数，来弥补matlab函数库在这方面的不足。(The MATLAB inside for calculating affine matrix commonly used RANSAC method, but more trouble calculation is relatively large, estimated by the least squares method to the affine matrix can greatly improve the efficiency, so give yourself in laboratory to write the estimated affine matrix function, to compensate for the lack of MATLAB Library in this area.)

对普通的粒子滤波和一种改进的粒子滤波算法进行比较，证明改进算法优越性(Of ordinary particle filter and an improved particle filter for comparison, to prove the superiority of improved algorithm)

通过matlab编写的几个关于psnr、mse的图像处理的小程序(Through several matlab written on the PSNR, MSE image processing of small procedures psnr_nmse_rms)

基于空域的脆弱水印，可以有效检测出图像发生篡改的区域(Airspace based on fragile watermarking can effectively detect the occurrence of tampering with the image of the region)

在基于的图像分割方法中，CV模型是一个非常重要模型。这是其实现ＭＡＴＬＡＢ源代码。(Based image segmentation method, CV model is a very important model. This is the MATLAB source code for its implementation.)

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.)