Harrispin

VC++开发的遥感影像拼接程序，两张示例图像，实现拼接线平滑的拼接算法。(VC++ development of remote sensing image mosaic program, two sample images to achieve a smooth stitching thread stitching algorithm.)

摄影测量源码，连续法的相对定向算法，提供实验数据和程序(Photogrammetric source, the relative orientation algorithm of the continuous method, the experimental data and procedures)

一个自适应的滤波处理的方法，可以对图像有很好的处理效果。(An adaptive filtering method of treatment can have a good image the effect of treatment.)

说明：  通过matlab源码实现图像的最佳自动阈值分割，所选算法是常见的大津法(Matlab source code through the realization of the best automatic image thresholding, the selected algorithm is a common method of Otsu)

图像处理课程设计——《人脸识别》，用matlab实现的，代码加实现，以及设计报告(Image processing designation of face recognize.)

一款VC++图像开场加载效果，向大家演示了几种图像装载的特效实现的方法，比如扫描显示、滑动显示、渐入显示和马赛克显示等，大家在使用一些幻灯片软件的时候，经学会看到类似的效果，如果你有一定的VC++基础，你可以借鉴一下本效果的具体方法，再次扩展，可以制作出一款带特效的图像查看器(The opening loading effect of a VC++ image to demonstrate the effects achieved in several image loading, such as scanning, slide show, getting into the display and mosaic display, we learn to look at some slides software to similar effect, if you have certain VC++ basis, you can learn about the effects of specific methods, extended again, can create the image of a band effects Viewer)

可根据需要自定义窗口形状，用于各种特效窗口开发(Customizable window shape, for a variety of special effects needed to develop window)

这是一部关于非高斯噪声中信号检测与估计的经典书籍，springer出版社出版，作者是S Kassam(This is a classical book about signal detection in non-Gaussian noise, by S Kassam)

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.)

一个自由、开源的图形库--FreeImage3.92最新版的中文参考(支持位图构件―例如调色板和数据位―的便易访问；将位图从一种位深度转换到另一种位深度；当有多幅位图页―例如TIFF―时访问位图的不同页；基本的位图处理，如旋转、翻转（flipping）和重采样，或点操作，如亮度和对比度调整；Alpha混合与合成（Compositing and blending）；FreeImage不支持：高级图象处理操作，如回卷（Convolution）和变换（Transform）；位图绘制； 矢量图形。)(a free, revenue graphics library-- the latest version FreeImage3 .92 reference to the Chinese (support bitmap elements- such as transfer shade and data spaces- the easy access; will be from a bitmap-depth conversion to another kind of depth; When a number of bitmap page- such as TIFF- Bitmap to visit the different pages; basic bitmap processing, such as rotation, Upset (flipping) and resampling, or point operations, such as brightness and contrast adjustments; Alpha mixed with the synthetic (Compositing and blending); FreeImage not support : Advanced image processing operation, If the response (Convolution) and transform (Transform); bitmap rendering; Vector graphics.))