matlab函数 localMaximum

通过python第三方库和matlab神经网络工具箱实现人脸识别(Face recognition using MATLAB and python through neural network)

一种精确地二维图像配准方法，实现亚像素的配准。(An accurate two-dimensional image registration method to achieve sub-pixel registration.)

PCNN实现降噪的不错 PCNN是很好的自动分割工具 PCNN是很好的自动分割工具(PCNN是很好的自动分割工具，)

很有用的gdal库，并且已经编译好。请多多指教!(It is a very good resource！Please download！！)

简单写的一些图像预处理（灰度增强、小波高通滤波、LBP、迭代阈值分割、种子生长法etc）和RGB 、纹理（相关矩阵）特征提取(Write some simple image pre-processing (grayscale enhancement, wavelet high-pass filter, LBP, iterative threshold segmentation, seed growth method etc) and RGB, texture (correlation matrix) feature extraction)

运用Perona-Malik各项异性扩散模型对二维图像进行去噪处理。该方法在有效的抑制噪声的同时能够保护图像的边缘。(The use of Perona-Malik Anisotropic Diffusion Model for the treatment of two-dimensional image denoising. The method in the effective suppression of noise at the same time to protect the edge of the image.)

分为行人检测，特征提取，行人跟踪三步，其中最主要的代码也是这个代码的中心是行人跟踪这一部分，我采用的是kalman滤波器进行行人下一帧位置的预测，可以很好的提高行人跟踪的鲁棒性，跟踪结果比较准确。(Into pedestrian detection, feature extraction, pedestrian tracking steps, which is the center of the main code of the code is pedestrian tracking this section, I kalman filter is used to predict the position of the next frame pedestrians, can be a good improvement pedestrian tracking robustness, tracking results more accurate.)

harris角点检测，并且实现两幅图像特征点的匹配，最终完成图像的拼接(harris corner detection, and realize two image feature point matching, the final completion of image stitching)

说明：  《数字图像处理（第三版）》课后习题答案，作者冈萨雷斯(Answers to Exercises after Class of Digital Image Processing (Third Edition),author Gonzalez)

对两帧图像进行ICM调试.包含内容：1估计姿态和摄像机内参数；2两幅图做四次金字塔；3利用输入特征点采用ransac算法估计姿态R, T。4sift特征匹配；5摄像机标定。(ICM images on two debugging. Contains: 1 Estimated posture and intrinsic parameters 2 two plans to do four pyramids 3 using the input feature points using ransac algorithm estimates gesture R, T. 4sift feature matching 5 camera calibration.)