MNF

2009年CVPR最佳论文（暗通道去雾算法）及其MATLAB代码(The best paper of 2009 CVPR conf.and its corresponding Matlab code. very useful for us.)

混沌系统中得logistic映射分岔图源程序，可以看到分岔效果，具有混沌特性(Chaotic systems have in the logistic map bifurcation diagram source, you can see the bifurcation effect the character of chaos)

做完边缘提取之后，有的边缘断断续续，需要进行边缘连接，将其连成完整线。(Done after edge detection, and some off the edge, the edge needed to connect, to link into the full line.)

基于matlab神经网络的遥感图像分类，使用了BP神经网络(Matlab neural network-based remote sensing image classification using BP neural network)

基于离散余弦变换的水印程序，大家看看有没有可以改进的地方(Discrete cosine transform-based watermarking process, everyone can see if there is any improvement)

P0301：数字图像矩阵数据的显示及其傅立叶变换 P0302：二维离散余弦变换的图像压缩 P0303：采用灰度变换的方法增强图像的对比度 P0304：直方图均匀化 P0305：模拟图像受高斯白噪声和椒盐噪声的影响 P0306：采用二维中值滤波函数medfilt2对受椒盐噪声干扰的图像滤波 P0307：采用MATLAB中的函数filter2对受噪声干扰的图像进行均值滤波 P0308：图像的自适应魏纳滤波 P0309：运用5种不同的梯度增强法进行图像锐化 P0310：图像的高通滤波和掩模处理 P0311：利用巴特沃斯（Butterworth）低通滤波器对受噪声干扰的图像进行平滑处理 P0312：利用巴特沃斯（Butterworth）高通滤波器对图像进行锐化处理 (P0301: digital image data matrix display and Fourier Transform P0302: two-dimensional discrete cosine transform image compression P0303: using gray transform method to enhance the contrast of the image P0304: histogram equalization P0305: Simulation images by white Gaussian noise and salt and pepper noise P0306: 2D median filtering function medfilt2 right by Salt and Pepper image noise filtering P0307: using MATLAB functions filter2 of noise images mean filtering P0308: Image Adaptive Filter Weiner P0309: use five different gradient Enhancement Act for image sharpening P0310: Images of the high-pass filtering and mask handling P0311: use Butterworth (Butterworth) low-pass filter on the noise in the image smoothing P0312: use Butterworth ( Butterworth) high-pass filter for image sharpening)

用matlab产生高斯，椒盐，泊松噪声图像的完整代码(poisson, gossip,noise,salt&pepper)

说明：  傅里叶变换中的角谱衍射理论，GS算法实现(Angle spectrum diffraction theory in Fourier transform, Realization with GS algorithm)

本算法主要采用变分贝叶斯求解图像忙恢复问题。(This package contains implementations of the MAP_k blind deconvolution algorithms described in the paper "Efficient Marginal Likelihood Optimization in Blind Deconvolution" Levin, Weiss, Durand and Freeman, )

视频图像处理，采用背景减除法中混合高斯建模进行视频前景和背景的分离(Video image processing, background subtraction method using Gaussian mixture modeling to separate the foreground and background video)