RF_positive_q

实现多种方法的全色和多光谱图像融合：（1）IHS变换（2）高通滤波（3）GIHS方法（4）小波变换（5）PCA （6）Brovey变换(A variety of methods of panchromatic and multispectral image fusion: (1) IHS transform (2) high-pass filter (3) GIHS method (4) wavelet transform (5) PCA (6) Brovey transform)

基于小波变换的使用SPIHT算法进行图像压缩，并对原有的算法进行优化(Based on wavelet transform using the SPIHT algorithm for image compression, and the original algorithm to optimize)

复杂场景中的红色交通标志牌检测与识别，结合颜色与圆形的标志牌定位，然后提取特征，最后用模板匹配的方法实现识别，内附图片和程序说明，对初学者有帮助(Red detection and recognition of traffic signs in complex scenes, the combination of colors and circular signs positioning, and feature extraction, the last with template matching methods to achieve recognition, included pictures and a description of the procedures for beginners)

matlab图像处理中中加入椒盐噪声的源代码。(add salt and pepper noise matlab source code.)

1.RAW格式转换为BMP格式 2.灰度线性拉伸 3.局部处理 4.几何处理 5.二值化 6.模板匹配 7.影像融合(1.RAW format converted to BMP format 2. grayscale linear stretch 3. local processing 4. geometric processing 5. binaryzation 6. template matching 7. image fusion)

基于Mean Shift的图像分割过程就是首先利用Mean Shift算法对图像中的像素进行聚类，即把收敛到同一点的起始点归为一类，然后把这一类的标号赋给这些起始点，同时把包含像素点太少的类去掉。然后，采用阈值化分割的方法对图像进行二值化处理 (Mean Shift Based on the process of image segmentation is the first to use the image Mean Shift algorithm for clustering of pixels, that is, to converge to the same point as a starting point to the category and then assigned to this type of labeling of these starting points, at the same time to contain too few pixels to remove the category. Then, using thresholding segmentation method of binary image processing)

一个很实用的GVF SNAKE程序，对于新手来说，可以通过代码的学习，掌握GVF SNAKE的意义和处理步骤(A very practical GVF SNAKE procedures, for the novice, it can be through the code learning, GVF SNAKE grasp the meaning and processing steps)

matlab code for processing of signals and images

单相光伏发电并网系统在孤岛运行时的simulink仿真(Islanding operation simulation)

说明：  光流法处理车辆视频，读取视频，分析单帧图片，得到光流图片(The optical flow method processes the vehicle video, reads the video, analyzes the single frame picture, obtains the optical flow picture)