shuangfengquyuzhi

本代码功能是将图像旋转任意角度，为进一步的图像处理做铺垫。(The code function is to rotate the image at any angle, laying the groundwork for further image processing.)

实现人脸识别及分割，使用人脸进行RGB颜色提取，并分层提取特征信息。(Realize face recognition and segmentation, use face for RGB color extraction, and extract feature information hierarchically.)

维纳滤波器仿真，是对基本算法原理的实现，没有考虑误差模型(Wiener filter simulation, the realization of the basic algorithm principle, without considering the error model)

System Generator中图像分割算法建模(Image segmentation algorithm for modeling in the System Generator)

说明：  整理了五种多曝光图像融合的代码，用于图像处理，图像去雾，有英文介绍(Five kinds of multi-exposure image fusion codes are sorted out.For image processing, image defogging, with English introduction)

稀疏表示，包括ksvd图像去噪，matlab程序，程序有详细注解，便于初学者学习，代码可以直接使用(Sparse representation, including ksvd image denoising， Matlab procedures, procedures are detailed notes, easy for beginners to learn, code can be used directly)

说明：  双峰法阈值分割。阈值分割法是一种基于区域的图像分割技术，原理是把图像象素点分为若干类。图像阈值化分割是一种传统的最常用的图像分割方法，因其实现简单、计算量小、性能较稳定而成为图像分割中最基本和应用最广泛的分割技术。它特别适用于目标和背景占据不同灰度级范围的图像。它不仅可以极大的压缩数据量，而且也大大简化了分析和处理步骤，因此在很多情况下，是进行图像分析、特征提取与模式识别之前的必要的图像预处理过程。图像阈值化的目的是要按照灰度级，对像素集合进行一个划分，得到的每个子集形成一个与现实景物相对应的区域，各个区域内部具有一致的属性，而相邻区域不具有这种一致属性。这样的划分可以通过从灰度级出发选取一个或多个阈值来实现。(Threshold segmentation)

1.运用Laplacian算子，基于二阶微分的图像增强，即拉氏变换法进行图像平滑 2.利用邻域平均法实现图像的平滑处理 3.利用Robert算子做锐化处理(1. The use of Laplacian operator, based on second-order differential of the image enhancement, that is, Laplace transform method for image smoothing 2. The use of neighborhood average method of smoothing image 3. The use of Robert sharpening operator to do)

说明：  当前论文主要考虑的是非信号依赖的高斯噪声下的图像恢复，本程序实现了泊松噪声下的图像恢复，泊松噪声为信号依赖噪声，能够更加有效逼近实际成像系统噪声。( This is the code that was used in the papers "A Nonnnegatively Constrained Convex Programming Method for Image Reconstruction", "Total Variation-Penalized Poisson Likelihood Estimation for Ill-Posed Problems", "Tikhonov Regularized Poisson Likelihood Estimation: Theoretical Justification and a Computational Method", "An Efficient Computational Method for Total Variation with Poisson Negative-Log Likelihood", "An Analysis of Regularization by Diffusion for Ill-Posed Poisson Likelihood Estimation," "An Iterative Method for Edge-Preserving MAP Estimation when Data-Noise is Poisson", and finally, "Regularization Parameter Selection Methods for Ill-Posed Poisson Maximum Likelihood Estimation". See my publications page for more details. The main algorithm is for nonnegatively constrained, regularized Poisson likelihood estimation. At this point you can choose Tikhonov, total variation regularization, and diffusion regularization. A number of other methods are also implemented. Regularizatio)

基于灰度图像处理的LSB密写的实现算法，matlab编程实现(Based on gray-scale image processing of LSB Steganography algorithm, matlab Programming)