声谱图

遗传算法/大津法/区域生长法/迭代法分割图像,有详细注释，适合学习(Genetic algorithm/dajin method/area growth method/iteration method image segmentation, and have the detailed notes, suitable for learning )

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.)

利用ICM方法得到基于MRF场的SAR图像分割(Achieve market segmentation ICM s MRF)

说明：  多基线SAR，InSAR相位解缠代码，Matlab版本，对应论文：Robust Two-Dimensional Phase Unwrapping for Multibaseline SAR Interferograms: A Two-Stage Programming Approach ，含数据、代码及验证结果(Multi baseline SAR, InSAR phase unwrapping code, matlab version, corresponding paper: robot two dimensional phase unwrapping for multibaseline SAR interferograms: a two stage programming approach, including data, code and verification results)

基于蚁群算法的图像边缘检测的matlab实现。里面有详细注释可以学习或者参考之用。(Based on ant colony algorithm for image edge detection matlab. There are detailed notes can learn or reference purposes.)

基于图像灰度共生矩阵的特征提取代码，程序实现0 45 90 135度4个方向的特征提取(GLCM based on image feature extraction code, the program achieved 04,590,135 degrees in four directions of the feature extraction)

采用超像素进行分割图像，利用到了超像素和Ncut的方法，采用了c与maltab混合编程。(Code to compute superpixels. use cncut and superpixel code for segmentation. Mex program c and matlab)

sift算法的核心，siftWin32.exe的源程序，可执行，可导入Matlab(The core of the SIFT algorithm, the source of siftWin32.exe, executable, can be imported to Matlab)

用于图像处理上的像素点之间相关性的计算，主要用于分析像素值之间的关联度。(For the calculation of the correlation between the pixels on the image processing)

基于adaboost的人脸检测算法，对于初学者来说用很大的帮助(Adaboost-based face detection algorithm for beginners great help)