Mallat_Atrous

matlab函数，将多维矩阵的极值找出并定位，图像处理经常用到，很简单很好用(matlab function, multi-dimensional matrix to identify and locate the extreme, often used in image processing, it is very simple to use)

基于FRFT的数字图像水印（lena示例）(FRFT based digital image watermark (lena example))

通过matlab编写的几个关于psnr、mse的图像处理的小程序(Through several matlab written on the PSNR, MSE image processing of small procedures psnr_nmse_rms)

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)

基于8×8分块得数字水印嵌入和提取算法。此算法已经通过调试，可以直接运行(Based on 8 × 8 sub-blocks have digital watermark embedding and extraction algorithm. This algorithm has been through debugging, you can directly run)

对二维码图像进行灰度化、中值滤波、二值化、边缘检测、霍夫变换等预处理(The two-dimensional code image is grayscale, median filter, two valued, edge detection, Hough transform and other pre-processing.)

自适应正则化的超分辨率重建程序，采用L1L2范数。(Adaptive Regularized super-resolution reconstruction of the program, using L1L2 norm.)

说明：  matlab实现人脸识别和虹膜定位 识别效果良好(Accurate eye location by MATLAB)

用AAM算法进行人脸特征点的标定，即对人脸的眼睛，眉毛，嘴巴，鼻子及脸的轮廓进行标记，此代码标记了68个特征点。(AAM algorithm for facial feature points calibration, calibration of this code is the 68 feature points, see the instance document.)

说明：  matlab实现图像的锐化，使用不同的算子分别对图像进行运算(Matlab achieve sharper images, the use of different operators were right image Operational)