target_pipei

基于DCT的数字水印算法 通过Arnold变换对水印进行置乱，增加了水印的鲁棒性，成功的实现了水印的嵌入和提取。(Arnold transform digital watermarking algorithm based on DCT watermark scrambling to increase the robustness of the watermark, the watermark embedding and extraction. )

说明：  图像处理,matlab文件，利用SURF进行图像拼接，完成图像配准(Image processing, matlab files, image stitching using SURF, image registration completed)

2维的基于互信息的图像配准算法，使用powell法作为优化算法(2-dimensional mutual information based image registration algorithms, the use of law as the optimization algorithm powell)

图像压缩实例，使用函数wdcbm2()获取信号压缩阀值(the example for image compression using wdcbm2() which is a wavelet function )

直方图的计算与显示分析图像、物体和视频信息过程，我们常把看到的物体用直方图（histogram）表示，直方图可以用来描述各种不同的事情，如物体的色彩分布、物体边缘梯度模板，以及表示目标位置的概率分布(Calculation and analysis of the histogram display images, objects and video information process, we often see objects with the histogram (histogram) indicates, the histogram can be used to describe a variety of different things, such as the color distribution of objects, object edges gradient templates, and the probability distribution of the target position)

图像位平面分割，高斯金字塔生成与复原，图像4因子下采样等基本操作，有详细的代码注释。(Image bit-plane partition, Gaussian pyramid generation and recovery, image down-sampling factor 4 basic operations, the code has detailed notes.)

梯度法计算指纹方向场，采用了三种方式：1、滑动块 2、自适应块 3、分割固定块(Gradient method is used to calculate the direction field of fingerprint, and three methods are adopted: 1, sliding block 2, adaptive block 3 and segmentation fixed block)

说明：  通过检测二维小波变换的模极大值点可以确定图像的边缘点，利用小波变换的多尺度性用于图像的边缘检测(By detecting modulus maxima point of two-dimensional wavelet transform we can determine the image edge points, using multi-scale nature of wavelet transform in image edge detection)

基于标准遗传算法的摄像头标定程序，内附readme(Standard genetic algorithm based on camera calibration procedures, containing readme)

k-均值聚类算法实现灰度图像分割，输入图像矩阵和聚类中心个数，返回为最终的聚类中心和图像中每个像素所属类的编号（对应于图像矩阵）(k-means clustering algorithm to achieve gray-scale image segmentation, the input image matrix and the number of cluster centers, the return for the final image of the cluster centers and their respective categories in each pixel number (corresponding to the image matrix))