Common-standard-pics

本代码可以实现图像的维纳滤波，经过调试无错误，对于学习图像处理有较好帮助。(This code can achieve the image filtering, error-free through the debugging, better for learning image processing help.)

二维图形图像处理，高斯平滑的源代码，图像预处理(Two-dimensional graphic image processing, Gaussian smoothing of the source code, image preprocessing)

图形图像正交变换，离散余弦变换，VC++实现。(Graphic image orthogonal transform, discrete cosine transform, VC++ to achieve.)

C++ based JPEG on grayscale image DCT -> Quantization -> ZigZag -> DPCM, Runlength,-> Entropy Coding

2016华为软件精英挑战赛，采用迪杰斯特拉算法，效率高，但需要自行修改(HUAWEI software challenge 2016)

阴影检测,基于OpenCV用于对图像中阴影的检测(Shadow detection, OpenCV for image shadow detection)

一个简单的虚线类，绘制各种虚线的C++类库，请看效果截图，可绘制出各种彩色的虚线效果。画横向或竖向虚线，以及对角线的虚线框效果，都是可以的，带有一个演示程序。(A simple dashed class, draw various dashed C++ library, see the effects shots, you can draw a variety of color dotted effect. Draw horizontal or vertical dashed line, as well as the effect of diagonal dashed box, are possible with a demo program.)

This is simple calculator program. I m making a GUI calculator interface in MFC. this program works pretty well.

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.)

对BMP文件进行图像处理，包括：边缘检测、频域变换、几何变换、图像变换校正、灰度变换、图像编码、平滑和匹配(BMP files for image processing, comprising: an edge detection, a frequency domain transformation, geometric transformation, image transformation correction gradation conversion, image coding, and matching the smooth)