repeatability_demo

：数字水印将感觉不到的信号嵌入到声频、视频和图像中以实现不同的目的。例如: 添加标题和版权保护。首先介绍 了有关数字水印的基本原理、重要属性及其主体框架。然后,将数字水印按不同角度划分为不同种类。讨论了各种各样的数 字水印算法以及数字水印在不同领域的应用,并简要介绍了对数字水印的攻击。最后,给出了数字水印当前的研究现状和发 展形式及前景。(: Digital watermark embedding imperceptible signals to the audio, video and images to achieve different purposes. Example: Add a title and copyright protection. Firstly, the basic principle about digital watermarking, and the main framework of the important attributes. Then, the digital watermark according to different angles into different types. Discussed a wide range of digital watermarking algorithms and digital watermarking applications in different fields, and a brief introduction of the digital watermarking attacks. Finally, the digital watermark of the current situation and development in the form of research and prospects.)

K-SVD的工具箱，使用非常简单，直接运行demo。有助于学习K-SVD，对初学者非常有用。(K-SVD Toolbox, easy to use and it is very useful for beginners.)

实现运动模糊图像的非盲卷积 分区域去模糊 有用(Implementation of motion blurred image blind deconvolution is useful to fuzzy areas)

freeimage library,freeimage library,(Freeimage library, freeimage library,)

sift算法的核心，siftWin32.exe的源程序，可执行，可导入Matlab(The core of the SIFT algorithm, the source of siftWin32.exe, executable, can be imported to Matlab)

一些常见的工程光学现象的模拟，如光的衍射，光的全息(Some common optical phenomena simulation projects, such as light diffraction, optical holographic)

计算一副图像，或者加噪声后图像信噪比和峰值信噪比，代码非常简洁方便，效率很高。(Calculate the image SNR and PSNR)

说明：  这个一个在目标检测中起定位作用的神经网络代码，不过这次我没有写使用教程，东西应该不难。(This is a neural network code that plays a role in target detection, but this time I did not write a tutorial, things should not be difficult.)

广度优先搜索和深度优先搜索在网络拓扑图上的实现。广度优先搜索是从某一节点开始，搜索与其线连接的所有节点，按照广度方向像外扩展，直到不重复遍历所有节点；深度优先搜索是从某一节点开始，沿着其搜索到的第一个节点不断深入下去，当无法再深入的时候，回溯节点，然后再在回溯中的某一节点开始沿另一个方向深度搜索，直到不重复的遍历所有节点。 (Breadth-first search and depth-first search in the network topology is realized. Breadth-first search is started from a node, searching all the nodes connected to its line, in accordance with the breadth direction as extracapsular extension, until no repeat traverse all nodes depth-first search is started from a node along its search to the first nodes deepening it, when it can not go any further, backtracking node, and then back again in the beginning of a node depth search in the other direction until the non-repetition of the traverse all nodes.)

联合特征选择和子空间相关性学习的跨模态检索，map优于典型相关性分析的跨模态检索(Joint Feature Selection and Subspace Learning for Cross-Modal Retrieval)