WAV-LSB-Watermark

IEEE:数字水印技术引论，其中将达哦水印技术的引出、算法发展、引用等(IEEE: primer on digital watermarking technology, which will lead to Oh watermark technology, algorithm development, quoted, etc.)

是一个很好的图像拼接程序，先用sift算法提取两幅图片的特征点再用算法筛去错配点，把匹配点用线连接起来，注意：主函数是match.m，运行主函数后在命令框输入运行match( image1.jpg , image2.jpg )(Is a good image stitching program, the first two pictures with the sift algorithm feature extraction algorithm and then weed out the wrong point with point, the match point with a line linking Note: The main function is match.m, after running the main function Enter the run command box match (' image1.jpg' , ' image2.jpg' ))

实现了交互式图像分割算法，只需手动标注标记点就可以实现图像分割(Interactive image segmentation algorithm, simply manually annotate the markers can be achieved to image segmentation)

运用harr特征+SRC（稀疏表示）分类实现的一种车辆检测方法，文件中提供了训练和测试车辆图片。由于时间原因，所用haar特征没有优化，维度过高，导致滑窗框图过慢，本代码只输出效果统计数据，以供大家参考学习稀疏表示在车辆检测中的应用。(Using harr feature+SRC (sparse representation) classification to achieve a vehicle detection method, the paper provides a training and test vehicle picture. Due to time reasons, the use of haar feature is not optimized, high dimension, resulting in sliding sash figure is too slow, the effect of the code only output statistics for your reference learning sparse representation in the vehicle detection.)

说明：  图像处理，图像分割，图像变换，图像特征提取，图像增强，图像编码压缩(Image processing, image segmentation, image transformation, feature extraction)

Ncut的文献及matlab源代码。基于图的分割非常好的一个算法(Ncut literature and matlab source code. Graph-Based Segmentation Algorithm for a very good)

评价图像边界的好坏，FOM值越趋于1质量越好。(figure of merit to objectively evaluate the performance of edge detectors)

关于基于Kruppa方程的摄像机自标定方法的两篇论文，相对于传统的标校方法，是一种新的相机自标定技术(About Kruppa equation based camera self-calibration method of two papers, as opposed to the traditional Calibration Method is a new camera self-calibration technique)

使用EM算法完成图像的分割，使用混合高斯模型，可以修改分类数。运行EM.m(Expectation Algorithm)

基于互信息的刚性配准，利用了Powell算法和黄金分割算法，效果还不错(Based on Mutual Information rigid registration, Powell algorithm and the use of the golden section algorithm, the results were good)