V4L2

matlab编写的截断半径45时，低通滤波器对与图像的影响，画图比较滤波前后的对比图。(matlab truncation radius of the preparation of 45, the low-pass filter and image of the effect of drawing the contrast to compare before and after filtering Fig.)

说明：  注：运行前自己准备图像，修改I = imread('')单引号中的路径 1. 给一张灰度图添分别添加高斯噪声和椒盐噪声。然后分别进行均值滤波和中值滤波，并把处理后的图片保存。 2. 图像频域处理，对图像进行傅里叶变换，进行高通滤波，显示处理结果。 3. 图像平移和旋转 4. 分别用OSTU阈值法和全局阈值法分割图像，然后进行腐蚀和膨胀处理，显示处理结果。(Note: Prepare the image by yourself before running, modify the path in single quotes of I = imread('')1. Add Gaussian noise and salt and pepper noise to a grayscale image. Then perform mean filtering and median filtering respectively, and save the processed pictures.2. Image frequency domain processing, Fourier transform of the image, high-pass filter, and display the processing result.3. Image translation and rotation4. Separate the image with OSTU threshold method and global threshold method, and then perform corrosion and dilation processing, and display the processing results.)

HOG（方向梯度直方图）图像特征提取，以lena图像作为示例(HOG (Histogram of Oriented Gradients) image feature extraction, image as an example to lena)

Image processing functions: Gamma correction Contrast stretching histogram equalization

利用最佳直方图熵法（KSW熵法）及穷举法实现灰度图像阈值分割(The best the histogram entropy method (KSW entropy method) and the brute-force method to achieve gray image threshold segmentation)

关于指纹图像处理的有关论文资料，希望各位同仁多多 指教。(Fingerprint image on paper deal with the relevant information, I hope that Tongren exhibitions.)

基于AM-FM纹理模型的图像特征提取方法研究(AM-FM texture model-based image feature extraction method)

susan角点检测算法的MATLAB程序实现(susan corner detection algorithm for implementation of the MATLAB program)

针对可见光与红外图像的特点和难点，提出了可见光与红外图像配准与融合中的关键技术，即: 使用新型的基于一维最大类间方差和最大连通性测量的图像分割方法对源图像进行分割来更好地实行图像粗 配准 使用新型的特征点提取方法，特征点的匹配及误匹配的消除来更好地实行图像精配准 采用新型的基 于区域的树状小波活性测度计算来实现树状小波图像融合 利用自生成神经网络来实现模栩图像融合. (For visible light and infrared images of the characteristics and difficulties, a visual and infrared image registration and integration of key technologies, namely: the use of new one-dimensional based on the largest variance between-class connectivity and the largest measuring method of image segmentation source image segmentation to better implementation of coarse image registration the use of a new type of feature point extraction method, feature points of the match and the elimination of false matches to better the implementation of image fine registration the use of new tree-based wavelet calculated to measure the achievement of the activity tree wavelet image fusion the use of self-generating neural network to achieve image fusion Xu mode.)

基于小波变换的水下图像目标检测论文加matlab实现代码(Wavelet-based underwater image target detection papers plus matlab code)