ssim

说明：  快速将图片裁剪为电脑壁纸和ipad壁纸尺寸，带预览(To cut pictures as PC or Ipad size conveniently)

局部二值模式，local binary pattern matlab代码(binary pattern matlab)

利用该函数可以对图像进行仿射变换，是不错的matlab源代码(Function can make use of the image affine transformation, is a good source code matlab)

图像融合中的平均梯度、相关系数、信息熵、交叉熵、联合熵、均方误差、互信息、信噪比、峰值信噪比、均方根误差、空间频率、标准差、均值、扭曲程度、偏差指数等等(Average gradient, correlation coefficient, information entropy, cross-entropy, joint entropy, mean square error, mutual information, signal-to-noise ratio, peak signal-to-noise ratio, root mean square error, spatial frequency, standard deviation, mean, distortion degree, deviation index, etc. in image fusion)

在此文档中，可以实现图形字母的识别，采用特征匹配的 方法，求取特征向量，一共13个(ocr)

求一个图像的最大内接矩形面积。 步骤： 1.相机标定。首先根据物像关系式求出其中的参数。注意参数求出后要进行参数校验。 2.从背景中分离出目标 3.边缘检测 4.目标形状参数计算。(For an image of the largest inscribed rectangle area. Steps: 1. Camera calibration. First of all object-image relationship in accordance with the parameters obtained. Attention to the parameters obtained after parameter calibration. 2. From the context of isolated target 3. Edge detection 4. Target shape parameters.)

提出了一种基于非下采样Contourlet 变换的自适应图像去噪方法 首先对噪声图像进行非下采样Contourlet 变换，得到各 个尺度各个方向子带的系数，再根据该系数的能量自适应地调整去噪阈值 实验表明，与Contourlet 多尺度阈值去噪 Contourlet 自 适应阈值去噪相比，该方法在保留图像边缘细节的同时，能提高图像的PSNR 值，减少了Gibbs 现象(A new adaptive method of image de-noising based on NonSubsampled Contourlet Transform （NSCT）is presented.Firstly， the noisy image is decomposed into a set of multiscale and multidirectional frequency subbands by NSCT， and then the threshold is adapted automatically according to the energy of subband coefficients.Compared with the multi-scale threshold using contourlet transform and using adaptive threshold based on contourlet transform， the simulation results show that the performance of this method is superior in PSNR， meanwhile it can maintain the image edge and reduce the Gibbs phenomen)

高斯有色噪声，有色噪声的谱估计及其在雷达中的应用(gauss noise)

说明：  改进了Criminisi算法，采用P-laplace算子作为数据项进行优先级计算，并有计算PSNR的功能(Improved Criminisi algorithm, using P-laplace operator as data items priority basis, and have calculated the functions of PSNR)

经典的斑块分析算法，计算Blob的源码，算法很好。(Classical plaque analysis algorithms to calculate Blob source code, algorithms very well.)