zernikeCT

在图像的DCT系数上嵌入信息，图像为常见的512*512大小的灰度图（实验所用图像为LENA.BMP）。嵌入的信息为一二进制Logo图（实验所用logo图为tj-logo.bmp），该图大小为32*32，共1024个Bit。 1. 在LENA图中嵌入水印，输出嵌入后的水印图像。 2. 对水印图像解码，输出解码后得到的logo图，并统计错误率。 3. 使用不同的嵌入强度进行嵌入，观察其对作品直觉效果和解码效果的影响，绘制相应的曲线。 4. 使用加入噪声、改变对比度、JPEG压缩等攻击方法对水印作品进行攻击，查看解码的效果。 (Information embedded in the DCT coefficients of the image, the image of the common 512* 512 size gray-scale (experimental image LENA.BMP). Information embedded in a binary Logo Figure (used in the experiment logo picture shows the tj-logo.bmp), the plot size 32* 32, 1024 Bit. LENA Figure embedded watermark, the watermark image output embedded. (2) logo watermark image decoding, the output decoded Figure statistical error rate. (3) using a different embedding strength for embedding, observe the works intuitive effects and decoding results, and draw the corresponding curve. (4) by adding the noise, change the contrast, JPEG compression attack methods to attack, to see the effect of decoding the watermark works.)

运用基于密度的聚类算法实现了超像素的分割(The segmentation of super pixels is realized by using the clustering algorithm based on density)

这是一个关于图像处理的程序，能够将像素比较低的图像变成分辨率高的图像.(This is a matter of image processing procedures, can be relatively low-pixel high resolution image into the image.)

利用棋盘格对相机进行标定，加入误差判定及像素空间到实际物理空间的距离计算(The camera is calibrated by checkerboard, the error is added and the distance of pixel space to the actual physical space is calculated)

该源码为目标检测和跟踪算法 包括： 1. 静态背景下的背景预测法目标检测 2. 静态背景下帧间差分法目标检测 3. Mean Shift目标跟踪方法 4. 重心多目标跟踪方法 (The source code for target detection and tracking algorithm include: 1 Static background background prediction target detection 2 Static background frame difference method for target detection 3. Mean Shift tracking method 4 multi-target tracking methods focus)

Pyramid methods in image processing

dib图像的读取，显示以及存储，能够运行(dib image read, display, and storage, and be able to run)

人民邮电出版社，《VC++数字图像处理典型算法及实现》-- 第9章图像分割。 包括图像的并行边界分割、串行边界分割、并行区域分割、串行区域分割、Canny算子的实现等源代码(Posts )

meanshift算法，及其在图像处理方面的应用(meanshift algorithm)

该类计算图像的主分量,特征值,特征向量,并且使用主分量重构.(The main components of such calculation of the image, feature values, feature vectors, and the use of principal component reconstruction.)