recover

说明：   最简单的差分格式有向前、向后和中心3种。 向前差分：f (n)=f(n+1)-f(n) 向后差分：f (n)=f(n)-f(n-1) 中心差分：f (n)=[f(n+1)-f(n-1)]/2(The easiest difference format forward, backward, and three kinds of centers. Forward differencing: f (n) = f (n+ 1)-f (n) Backward difference: f (n) = f (n)-f (n-1) Central difference: f (n) = [f (n+ 1)-f (n-1)]/2)

matlab 归一化相关系数，可用于模板匹配(matlab normalized correlation coefficient)

TV模型用于图像修复，能够实现较好的图像修复效果，是基于偏微分方程的方法(TV model for image restoration, and to achieve better image restoration effect is a method based on partial differential equations)

进行分数傅立叶变换的算法，通过该算法可以对函数进行任意分数阶傅立叶变换(For the fractional Fourier transform algorithms, the adoption of the algorithm can function for arbitrary fractional order Fourier transform)

利用基于直方图的自适应阈值方法实现分割前景与背景(Segmentation of foreground and background using histogram-based adaptive threshold method)

根据Dalal提出的HOG特征算法编写，代码简单，注释清楚，根据所处理图像的名称路径修改后可生成36*105的特征向量。(The algorithm proposed by Dalal HOG feature writing code simple, clear annotation feature vector can generate 36* 105, modified according to the name of the image processing path.)

C#连接摄像头，可以干好多事情了，自己扩展，这个只是个demo

matlab图像处理代码，利用分裂、合并算法进行图像的分割，含m文件和GUI(matlab image processing code, using split, merge image segmentation algorithms, including documentation and GUI m)

Abstract—Noninvasive ultrasound imaging of carotid plaques allows for the development of plaque-image analysis methods associated with the risk of stroke. This paper presents several plaqueimage analysis methods that have been developed over the past years. The paper begins with a review of clinical methods for visual classification that have led to standardized methods for image acquisition, describes methods for image segmentation and denoizing, and provides an overview of the several texture-feature extraction and classification methods that have been applied. We provide a summary of emerging trends in 3-D imaging methods and plaque-motion analysis. Finally, we provide a discussion of the emerging trends and future directions in our concluding remarks.

说明：  二值化程序：实现自适应二值化。效果较好，二值化后图片较清晰(Binarization process: the realization of adaptive binarization. Better, after binarization clearer picture)