picture-calibration

双目匹配计算视差，生成深度图。（前提是用自己标定好的摄像头拍的图片，导入内外参数然后进行立体匹配）(Binocular matching calculates parallax and generates depth map.(The premise is to take a picture with your own calibrated camera, import internal and external parameters, and then stereo matching))

实验目的： 1） 图像水平集合 2） 图像加密算法 3） 边缘提取 4） 噪音图像的产生 （2）显示图像，理解图像的模型 （3）使用图像的不同格式，理解图像压缩的意义 （4）对图像做简单的操作 本次实验需要熟练使用以下几个MATLAB命令： imread, imwrite, imshow,figure (Experimental purposes: 1) the level of collection of image 2) image encryption algorithm 3) Edge 4) noise generated images (2) display images, understanding image model (3) the use of images in different formats, understanding the significance of image compression (4) image to do a simple experiment needs to operate the skilled use of the following MATLAB command: imread, imwrite, imshow, figure)

说明：  用matlab编写的图像复原源代码，采用维纳滤波复原技术，可对模糊和加噪的图像实现精确复原。(Prepared using matlab source code image restoration using Wiener filter restoration technology, can be vague and processors realize accurate image noise resilience.)

graph cut 源码实现,yuri Boykov大牛的经典之作(graph cut algorithm matlab implementation)

说明：  本代码使用MATLAB编写的基于GST模型的红外弱小目标检测代码(% This source code is for infrared small target detection method based on Generalized Structure Tensor (GST). % If you use this code in your publications, please cite:)

说明：  JPEG2000 的一个实现，期中，wavelet.dll是提供的功能接口。(An implementation of JPEG2000, period, wavelet.dll is to provide a functional interface.)

说明：  经典的大津otsu算法在matlab中的实现程序，每一步都是经典步骤。(Otsu classical Otsus algorithm in matlab implementation process, each step is the classical steps.)

实现肺实质初始分割及采用滚球法（形态学开运算）进行修补肺实质轮廓凹陷。(Achieve initial segmentation and the use of the pulmonary parenchyma ball method (morphological opening operation) to repair the lung parenchyma contour depression.)

关于运动目标检测基础算法，混光流法合高斯模型、均值法、及帧间差分法(Moving target detection algorithm based on mixed Gaussian model optical flow together, mean method, and the inter-frame difference method)

Visual Tracking via Locality Sensitive Histograms.基于局部敏感直方图的目标跟踪算法，该算法在CVPR2013中出现，算法较简单但却非常有效，值得各位研究视觉跟踪算法的同行研究(Visual Tracking via Locality Sensitive Histograms)