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压缩传感，MATLAB，信号重建，正交匹配追踪，打破乃奎斯特定理(Compressed sensing, MATLAB, signal reconstruction, orthogonal matching pursuit, breaking the Nyquist Theorem)

ViBe算法是由Olivier Barnich 和 Marc Van Droogenbroeck在2011年提出的一种背景建模方法。该算法采用邻域像素来创建背景模型，通过比对背景模型和当前输入像素值来检测前景.(ViBe algorithm is a background modeling method proposed by Olivier Barnich and Marc Van Droogenbroeck in 2011. The neighborhood pixels are used to create the background model, and the foreground is detected by comparing the background model and the current input pixel values)

基于边缘特征的图像配准算法源码 基于边缘特征的图像配准算法是将不同时间、不同的传感器（成像设备）或不同条件下（天候、照度、摄像位置和角度等）获取的同一场景的两幅或多幅图像根据其边缘特征进行匹配、叠加的处理，最终生成一幅全景图像的方法。该方法具有抗噪性强，匹配速度快，误匹配率低，适用于多种类型的图像等优点，主要可以运用于以下领域： （1）军事研究领域，如飞行器辅助导航系绞、武器投射系统的末制导以及寻地等应用研究； （2）医学图像分析，如数字剪影血管造影DSA血管造影术、肿瘤检测、白内障检测、CT、MRI、 PET、 SPECT图像结构信息融合； （3）模式识别，如特征识别、波形分析、签名证实、目标物运动跟踪、序列图像分析等； （4）计算机视觉，可用于目标定位、自动质量控制等； （5）遥感数据分析，多电磁波段图像信息融合，如多谱段的等场景分类、定位和识别定义好的或已知特征的场景、自然资源监控、核生长监控、市区增长检测等。 本算法实现使用VC++6.0为开发环境，目前只支持灰度图像，感兴趣的朋友可以进一步扩展。(Image registration is a fundamental problem in image processing, which is a process to match two or more images of the same scene taken at different times, from different viewpoints, or by different sensors. Image registration is an important technique for a great variety of applications such as medical image analysis, computer vision, remote image data analysis, image information fusion, and the recovery of the 3–D characteristics of a scene.)

canny边缘检测的matlab实现，用到了基于Otsu算法的自适应阈值选取(canny edge detection)

利用16幅高低温图像，计算红外图像中经常用到的两点校正系数。是平时工程中的仿真程序。希望对大家有用。(The use of 16 high and low temperature images, the calculation of infrared images of two frequently used correction factor. Is the usual engineering simulation program. Hope useful for everyone.)

canny边缘检测的步骤： 1，生成高斯核，与图像做卷积 2，计算梯度图像 3，非极大值抑制 4，双阈值法和连接边缘(Canny edge detection steps: 1, Generate Gaussian kernel, convolution with the image 2, calculate the gradient image 3, non-maximal inhibition 4, double threshold method and connect the edge)

该代码用于对错误匹配点进行过滤操作，即去除错误的匹配点(The code is used to remove the wrong match points,and make sure the right matching.)

W.T.Freeman 经典 基于例子的超分辨率重构matlab源码，图片自己可加，经测试可用(WTFreeman classic example of super-resolution reconstruction based on matlab source code, images themselves can be added, the test can be used)

说明：  用于特征提取，比较传统的一个方法，应用范围广，适合初学者(For feature extraction)

手持式摄像机在使用时常常会受到使用者有意无意抖动的影响,从而影响成像效果，造成录制视频的不稳定及跳动问题，尤其是在使用者在一场景中特写或者跟踪某一具体目标时，使用者通常不能准确定位到或者估计出运动目标的位置，从而造成目标在视频中位置的不稳定，造成视频的主观效果变得不理想。 为了解决这一问题，我们需要设计一种算法来识别这种无意义的运动并设法通过补偿的方式来使得场景中的目标物体保持位置稳定的状态。 手持式摄像机捕获的视频通常都会受到抖动的影响，这严重的影响视频的主观效果。 这里提出的算法可以可靠的用于数字视频的去抖动。这个算法通过识别这些意外的抖动并且利用运动补偿的方法来获得一个较好的视频输出。 这个系统可以分为三个模块：（1）运动估计模块；（2）抖动识别模块；（3）运动补偿模块。 注：代码在matlab 7.7.0(R2008b)运行通过 [1] F Vella, A Castorina, M Mancuso. Digital image stabilization by adaptive block motion vectors filtering, IEEE Transactions on Consumer Electronics, 2002(Handheld cameras are often used by the user intentionally or unintentionally, the influence of jitter affect the imaging results, resulting in instability and beat the problem of recording video, and especially in the user in a scene close-up or tracking a specific target,users often can not accurately navigate to estimate the location of the moving target, resulting in the subjective effects of target location of the instability in the video, resulting in video not ideal. In order to solve this problem, we need to design an algorithm to identify such a meaningless exercise and try to make the object in the scene to keep the position stable state by way of compensation. The handheld camera captured video usually subject to the influence of jitter, the subjective effect of which seriously affect the video. The algorithm proposed here can be reliably used for digital video to jitter. This algorithm by identifying the jitter of these accidents and the use of motion compensation m)