bandlet-denoising

扩展卡尔曼滤波的基础代码，有详细的注释，结合卡尔曼滤波的基本原理，就能很好的理解卡尔曼滤波过程了。(Extended Kalman filter based code , there are detailed notes , combined with the basic principles of Kalman filtering , we can well understand the process of Kalman filtering )

基于MRF模型的变化检测算法仿真 MRF建模用于SAR去噪，再通过EM算法实现变化检测(MRF model-based change detection algorithm simulation)

基于模糊对比度的图像增强方法，大致过程仍然是先把图像从空间域映射到模糊域，在模糊域内通过定义一个局部对比度算子，然后通过对凸函数的加强来放大像素邻域的各像素之间的差异。 (Based on the fuzzy contrast image enhancement method, the general process is still the first images from space domain is mapped to the fuzzy field in fuzzy field through the define a local contrast operator, and then the convex function to enlarge the strengthening of pixels each neighborhood pixel differences. )

程序实现了三种去噪算法：BLS-GSM/BM3D/NLM，评价指标为PSNR/SSIM.(Program implements three de-noising algorithm: BLS-GSM/BM3D/NLM, with evaluation of PSNR/SSIM.)

使用背景差分法实现一般视频的前景运动目标提取和检测。(The background difference method is used to realize the extraction and detection of the foreground moving target in the general video.)

说明：  水平集边缘检测代码，利用了变分法进行优化和处理，实现了图像的快速边缘检测(Level set edge detection code is optimized and processed by using variational method, and fast edge detection of image is realized.)

数据库是由10个人的7种正面表情组成的213幅灰度图像，图像是以大小为256256的8位灰度级存储的，格式为.tiff型，平均每个人每种表情有2到4张。( the JAFFE database[11] which is composed of 213 images of female facial expression corresponding to 10 distinct subjects. Each image is stored at a resolution of 256×256 pixels and 8-bit gray level. Each subject in the database is represented with 7 categories of expression (angry, disgust, fear, neutral, sadness, happiness and surprise). )

说明：  matlab近红外光谱进行掺假判断，运用plsda建模可以进行真假鉴别(The near infrared spectrum of MATLAB is used to judge the adulteration, and plsda modeling can be used to identify the authenticity)

多边形填充作业.rar(filled polygon operations. Rar)

卡尔曼滤波的一个典型实例是从一组有限的，包含噪声的，对物体位置的观察序列（可能有偏差）预测出物体的位置的坐标及速度。在很多工程应用(如雷达、计算机视觉)中都可以找到它的身影。同时，卡尔曼滤波也是控制理论以及控制系统工程中的一个重要课题。(A typical example of the Kalman filter, from a limited set, containing the noise, the position of the object observed sequence (there may be deviation) to predict the coordinates of the location and speed of the object. Its presence can be found in many engineering applications (such as radar, computer vision). Meanwhile, the Kalman filter is control theory, and control is an important topic in systems engineering.)