LLE

matlab下图文并茂的分析了fft算法，分析了如何从频谱如何看频率，相位，幅值(Here to enter through the abundant of matlab analyzed fft, and analyzed from the frequency spectrum how to see that phase, should be translated text)

说明：  matlab 实现高光谱图像处理中omp算法(OMP algorithm in hyperspectral image processing based on MATLAB)

说明：  在一图像中加入噪声，是超分辨率中的一个重要步骤哦(noise)

自己编写的三维目标跟踪粒子滤波程序，比较基本，可以帮助学习理解。(I have written three-dimensional target tracking particle filtering procedures, basic, can help study and understand.)

图像预处理：分水岭分割算法，图像灰度化、高斯平滑、均衡直方图、图像对比度增强(Image Pre-processing: a watershed segmentation algorithm, images of gray-scale, Gaussian smoothing, balanced histogram, image contrast enhancement)

说明：  利用python写的简单降噪程序（根据一个点A的RGB值，与周围的8个点的RBG值比较，设定一个值N（0

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.)

实现dicom和bmp之间的转换。适合医学图像中的最初学习。(transformation between dicom and bmp image.)

计算原始图像和过滤噪声后的图像的峰值信噪比(peak signal to noise ratio of image)

该程序通过雅可比矩阵求解Rossler系统的李雅普诺夫指数指数，并绘制了其频谱图。(The program solves the Lyapunov exponent of Rossler system by Jacobian matrix and draws its spectrum.)