135475202135

2009年CVPR最佳论文《Single image haze removal using dark channel prior》暗原色图像去雾的算法实现。与原文不同的是本程序没有完成最后matting细化效果的部分，但仍能够达到视觉上可以接受的去雾效果。计算机视觉课程作业。工程运行于VS2008环境，需要OpenCV支持。Debug目下exe文件可以直接双击运行查看结果。(CVPR 2009 Best Paper " Single image haze removal using dark channel prior" to the dark fog of the primary image algorithm. The difference is that with the original program did not complete the final matting refinement part，yet haze-removal result is visually acceptable. Visual course work. This project runs under VS2008 with OpenCV. Double click the exe file under Debug folder to check the final result.)

数字水印处理，嵌入、提取、认证，可以在图形，视频和文本中添加数字水印，增强文档的保密，防止泄密(Digital watermarking processing, embedding, extraction, authentication, can be in graphics, video and digital watermarking to add text to enhance the confidentiality of documents to prevent leak)

图像处理的指针式仪表识别，利用OPENCV库，MFC对话框程序(Image processing pointer instrument identification, the OPENCV libraries, MFC dialog program)

混合高斯(Mixture of Gaussian, MOG) 背景建模算法和Codebook 背景建模算法被广泛应用于监控视频的运动目标检测问题, 但混合高斯的球体模型通常假设RGB 三个分量是独立的, Codebook 的圆柱体模型假设背景像素值在圆柱体内均匀分布且背景亮度值变化方向指向坐标原点, 这些假设使得模型对背景的描述能力下降. 本文提出了一种椭球体背景模型, 该模型克服了混合高斯球体模型和Codebook 圆柱体模型假设的局限性, 同时利用主成分分析(Principal components analysis, PCA) 方法来刻画椭球体背景模型, 提出了一种基于主成分分析的Codebook 背景建模算法. 实验表明, 本文算法不仅能够更准确地描述背景像素值在RGB 空间中的分布特征, 而且具有良好的鲁棒性.(The background modeling algorithm of mixture of Gaussian (MOG) and codebook is widely used in moving object detection of surveillance video. However, the ball model of MOG usually assumes that the three components of RGB are independent, while the cylinder model of codebook assumes that the value of background pixel is distributed uniformly within the cylinder and the changing direction of brightness points to the origin of the coordinate system. These assumptions reduce the descriptive capability for background modeling. Therefore, the paper proposes an ellipsoid- based background model, which overcomes the MOG and codebook0s limitations. By using principal component analysis to depict the ellipsoid background model, a novel PCA-based codebook background modeling algorithm is proposed. Experiments show that this algorithm can not only give more accurate description of the distribution of background pixels but also have a better robustness.)

这是一款适用于初学者的应用程序,它可以帮助我们处理图形图像(This is a beginner for the application, it can help us to deal with graphic images)

关于包络跟踪测试解决方案的说明。介绍了所需的相关仪表以及之间的同步通信(Envelope Tracking)

打开24位彩色bmp文件, 显示该图像 将图像内容顺时针旋转90度后显示出来 将图像分成等大小的4块，将第1和第3块像素互换后保存 将旋转后的图像转换成灰度图像显示，并保存 对灰度图像求Sobel边缘图，显示出来，并保存 对灰度图像进行Gaussian平滑，并保存（需要体会平滑的作用） 对灰度图像进行2值化(Open 24-bit color bmp files, displays the image will rotate clockwise image content displayed image is divided into four equal-sized 90 degrees, the first and three pixels after swap to save the rotated image conversion ashes of the image display, and save images to grayscale seeking Sobel edge map is displayed, and save the gray image Gaussian smoothing, and save (experience required smoothing effect) grayscale image binarized)

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.)

C++和halcon结合，用于图形处理时进行三相机标定(C++ and halcon combined for three camera calibration)

数字图像处理边缘检测算法VC源码，里面包括多种检测算子(Digital image processing edge detection algorithm VC source code,Which includes a variety of detection operator )