taosang_v55

基于KSvd算法的图像重建，包括图像、代码、字典等(K-SVD dictionary training algorithms)

设置位置断点跟踪程序，VC++精选编程源码，很好的参考资料。(Set breakpoint location tracking procedures, VC++ programming source code, a good reference.)

立体视觉中的相机标定程序！很好用的张正友方法标定程序(stereo vision of the camera calibration procedure! Zhang good is the method of calibration procedures Friends)

软硬阈值及软硬阈值折中法对bumps信号去噪，另外包含信噪比以及均方误差的求解。(Soft and hard threshold and soft and hard threshold compromise the bumps signal denoising, the other contains the signal to noise ratio and mean square error to solve.)

主要研究了彩色图像数字水印算法，在DCT域进行了水印的自适应嵌入和提取，并用Matlab进行了仿真实验，测试算法的性能(The main color image watermarking algorithm in the DCT domain adaptive watermark embedding and extraction, and with the Matlab simulation experiment to test the performance of algorithm)

红外焦平面探测器输出图像信噪比计算和分析(Infrared focal plane image detector output signal to noise ratio calculation and analysis)

Stereoscopic video coding

基于直接最小二乘法的椭圆拟合程序，比较实用，适用于图像处理，椭圆拟合方面研究的初学者(Direct least square method based on ellipse fitting procedure more practical for image processing, aspects of ellipse fitting for beginners)

EDLines是一种快速直线检测算子，2012年在ICCV上提出，也是目前处理直线检测最快的算法之一，该算法包含三个步骤：（1）边缘提取：利用Edge Drawing (ED)算法[28,29]从灰度图像中提取边缘片段；（2）线段检测：利用最小二乘法提取直线段；（3）线段确认：遵循Helmholtz定律，从已提取的直线段中摒弃虚假线段。EDLines算法的优越性得益于Edge Drawing (ED)算法能够从灰度图像中准确、快速、稳定地提取出光滑、完整的边缘片段。Edge Drawing (ED)算法包含以下步骤： （1）采用size=5*5,σ=1的高斯核对灰度图像进行平滑滤波，去除噪声； （2）采用一种常用的梯度算子，如Prewitt、Sobel或Scharr等计算平滑后图像中每个像素点的梯度幅度和梯度方向； （3）将梯度图中邻域内幅度最大的像素点标记为锚点，这些锚点成为图像边缘点(edge elements)的概率很大； （4）将相邻的锚点连接成边缘线。从一个锚点起始，ED利用相邻像素的梯度幅度和方向在梯度为最大值的锚点之间游走。 (Edge Drawing (ED) is our recently-proposed, novel, fast edge detection algorithm. What makes ED stand out the existing edge detectors, e.g., Canny, is the following: While the other edge detectors give out a binary edge image as output, where the etected edge pixels are usually independent, discontinuous entities ED produces a set of edge segments, which are clean, contiguous, i.e., connected, chains of edge pixels. Thus, while the output of the other edge detectors requires urther processing to generate potential object boundaries, which may not even be possible or result in inaccuracies ED not only produces perfectly connected object boundaries by default, but it also achieves this in blazing speed compared to other edge detector.)

对于传统去噪模型的大幅改进，之前的模型都会出现阶梯效应的现象，采取了新的模型对图像进行建模，有效改善了图像去噪图像修复等过程中引入的阶梯效应，而且一定程度上对于图像纹理的修复也有很大的作用(For significantly improve the traditional de-noising model, the model will appear before the phenomenon of the staircase effect, to take a new model for image modeling, effectively improved the staircase effect denoising image restoration process introduced, and to a certain extent for texture of repair also has a significant role)