基于otsu的自适应阀值canny边缘检测 otsu-canny

说明：  打包的二维三维图形图像处理源代码 稀有资源(packed 2D and 3D graphics processing source of scarce resources)

在文档下打开一个位图文件，重新绘制，放大并使其二值化显示，()

最经典之做，保证别人没有上传过 实现文章 “GrabCut" Interactive Foreground Extraction using Iterated Graph Cuts 用graphcut实现图像分割，效果非常好(The most classic to do to ensure that other people do not realize uploaded article GrabCut Interactive Foreground Extraction using Iterated Graph Cuts with graphcut realize image segmentation, has very good results)

说明：  关于图像处理里的一些应用，将视觉相应算法应用到工程实际中，详细解说了算法在这里面的一些应用，很实用。(On some applications in image processing, the visual corresponding algorithm is applied to the engineering practice, a detailed explanation here below in some applications, the proposed algorithm is very practical.)

BMP转位图 6410 logo bmp-C(BMP bitmap transfer)

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.)

说明：  直方图均衡化,直方图均衡化vc++源代码(histogramequalization)

说明：  XYZ视频图像压缩编码的应用原理与实际生活应用 (XYZ video image compression encoding)

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.)

Matlab time-frequency analysis supporting the source code of chapter 12, please share