fengejiance

利用matlab进行插值法亚像素边缘检测，提取零件轮廓(Subpixel edge contour extraction)

说明：  对局部放电进行小波变换模式识别，解决放电破坏设备问题(Wavelet Transform Pattern Recognition for Partial Discharge)

VC计算机图形学原理及算法教程 VC计算机图形学入门教程(VC theory and algorithms of computer graphics computer graphics tutorial Tutorial VC)

Jsteg算法实现，Jsteg是一种基于JPEG的常用信息隐藏算法步骤如下: 首先，把掩体图像分为不重叠的8*8的子块，对每一子块进行DCT并对变换得到的DCT系数进行量化 其次，将待隐藏的信息进行加密，将加密结果嵌入到量化后值不为0，1或-1的DCT系数的最 低有效位(LSB)中，其嵌入顺序是按zigzag扫描顺序进行的。最后，用JPEG的嫡编码(包括哈夫曼编码，游程编码及DPCM)对嵌入秘密信息后的每一子块进行编码，从而得到一个含有秘密信息的JPEG stego文件。(Jsteg Algorithm)

image compression using dwt and dct

这是一个很全的云模型图像处理，功能全，已运行(This is a good use of the cloud model program, function, good effect, has been in operation)

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.)

利用高斯混合模型进行视频前景运动目标的提取！请使用自己的AVI文件。(extract the foreground moving object using the Gaussian mixture model)

自适应的图像增强，使用matlab编的代码，实现一篇核心文献的算法(Adaptive image enhancement using matlab compiled code to achieve a core algorithm literature)

编程实现二维8*8图像块的DFT，DCT变换 输入一副RGB图像，将其转化为YCbCr颜色空间，然后对Y分量做分块DFT变换，保存为灰度图像，统计计算时间 编程实现8*8块DCT变换,然后分别显示，当使用64个DCT系数里面的一些系数进行重构，比较其质量；同时熟悉采用FFT来实现DCT变换的思想，并显示2维8*8DCT变换的基函数图像(Programming the DFT, DCT transform of two dimensional 8*8 image block Input a pair of RGB images, transform it into YCbCr color space, then divide the Y component into block DFT transform, save as gray image, and calculate the calculation time The 8*8 block DCT transform is implemented by programming, and then it is shown that when using some coefficients in 64 DCT coefficients, the quality is reconstructed. Meanwhile, the idea of DCT transformation is familiar with FFT, and the base function image of the 2 dimensional 8*8DCT transform is displayed.)