Colored-Noise-Kalman-Filter

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))

四叉树分解算法对ＲＧＢ彩色图像进行分割，ＭＡＴＬＡＢ代码，包括实验图片(Quad-tree decomposition algorithm RGB color image segmentation, MATLAB code, including test images)

说明：  《80例上手Delphi7编程_06图形图像多媒体》书附盘。包括镜框、渐变色、动画、艺术字等图像处理示例。("80 cases easily Delphi7 programming _06 imagery multimedia" book with CD. Including the frame, graded color, animation, art images, such as word processing examples.)

本程序可实现维纳滤波，可应用于反褶积等反问题的求解过程中，是非常简单实用的(This program can be realized Wiener filter can be applied to deconvolution inverse problems and the process is very simple and practical)

- 1、限幅滤波法（又称程序判断滤波法） 2、中位值滤波法 3、算术平均滤波法 4、递推平均滤波法（又称滑动平均滤波法） 5、中位值平均滤波法（又称防脉冲干扰平均滤波法） 6、限幅平均滤波法 7、一阶滞后滤波法 8、加权递推平均滤波法 9、消抖滤波法 10、限幅消抖滤波法 (- 1, limiting filtering method (also known as filtering method to determine the procedure) 2, the median filtering method 3, the arithmetic average filtering method 4, the average recursive filtering method (also known as the moving average filtering method) 5, with a median value of the average filter Act (also known as anti-pulse interference average filtering method) 6, limiting the average filtering method 7, the first order lag filtering method 8, the weighted average recursive filtering method 9, extinction Buffeting filtering method 10, limiting consumer Buffeting filtering method)

用于分割2D、3D图像的可交互graph cut程序，纯matlab实现，不含C++(An interactive graph cut program segmenting 3D images)

利用数学形态学对云层背景下的目标进行检测识别，有两种方法。 (Using mathematical morphology of clouds in the context of target identification, there are two ways.)

说明：  虚拟示波器实现示波器的功能 数据采集 处理 存储(Virtual oscilloscope)

说明：  SIFT，即尺度不变特征变换（Scale-invariant feature transform，SIFT），是用于图像处理领域的一种描述。这种描述具有尺度不变性，可在图像中检测出关键点，是一种局部特征描述子。 该方法于 1999 年由 David Lowe 首先发表于计算机视觉国际会议（International Conference on Computer Vision，ICCV），2004 年再次经 David Lowe 整理完善后发表于 International journal of computer vision（IJCV） 。截止 2014 年 8 月，该论文单篇被引次数达 25000 余次。(来自百度)(SIFT, namely Scale-invariant feature transform (SIFT), is a description used in the field of image processing. This description has scale invariance and can detect key points in images. It is a local feature descriptor. This method was first published by David Lowe at the International Conference on Computer Vision (ICCV) in 1999 and published in the International Journal of Computer Vision (IJCV) in 2004 after it was sorted out and perfected by David Lowe again. As of August 2014, more than 25,000 citations have been cited. (From Baidu))

作者:J.Kittler and J.Illingworth KI阈值算法(Author：J.Kittler and J.Illingworth 1986)