Kriging

一种红外图像自适应对比度增强方法的仿真，绝对的真实，看到那些骗下载分的人恶心。需要自适应修改阈值T和A1，A2的值(An adaptive contrast enhancement method of infrared image simulation, absolutely true, see those who cheat download points. Need adaptive modified threshold T and A1, A2)

区域图象分割的源码，基于区域增长的分割的代码(Image segmentation of the source region, regional growth based on code division)

利用Matlab编写的基于hough变换的椭圆检测程序，已经运行过的，附图(Written in Matlab, hough transform based ellipse detection procedure has been run off, with photos)

fcm医学图像分割算法，适应于不规则医学图像的分割，已经调试成功，可以运行，很好。相信会对您有帮助。(fcm medical image segmentation algorithm, adapted to irregular medical image segmentation, has been successful debugging, you can run, very good. Believe will help you.)

本文主要研究基于水平集方法的活动轮廓模型图像分割，在回顾活动轮廓模 型发展的基础上，介绍了曲线演化理论及其水平集方法，证明了水平集方法可以 有稳定的数值实现方式且其处理拓扑变化的自然性，进一步引出了变分水平集方 法。 本文介绍了两种不同的几何活动轮廓模型：基于梯度信息的李纯明模型以及 基于区域信息的 Chan-Vese 模型（C-V 模型）。在分析上述两模型的优缺点上，提 出了一种改进的 C-V 模型，改进模型引入了距离约束项，同时对基于区域的外部 能量项进行了改进，使得水平集函数重新初始化寓于模型的演化之中，分割结果 对参数的依赖性减小。 (This paper mainly study image segmentation of active contour model based on level set. After reviewing the development of the active contour model, curve evolution and level set method are presented, then we proved that the level set method has a stable numerical realization and can describe the topology change of the contour naturally, in addition we introduce level set of variational method. We introduce two different GAC models in this paper: Li Chunming model which is based on gradient information and Chan-Vese model （C-V model） which is based on region information. Based on the drawbacks and advantages of these two models, we improve the C-V model by adding penalizing energy term of signed distance function, at the same time, mending the external energy term which based on region information, then the re-initialization of the level set can accomplish in the model evolution, and the degree of the segmentation result depend on the parameters decline. )

几种图像增强的方法，有双直方图均衡，函数均衡等几种方法(several image enhancement methods, a double histogram equalization, function balance methods)

说明：  matlab水果识别器，形态学，识别五种水果，要求背景较简单边缘明析(matlab fruit recognizer, morphology, recognition of five kinds of fruits, requiring simple background and edge)

该算法首先通过字典学习得到含噪图像的冗余字典，然后对相似的图像块进行聚类构成块群，并通过迭代收缩和L1正则化约束，对同类的图像块在字典上进行稀疏表示，以达到降噪的目的。实验结果表明，在常规的图像处理上，本文提出的算法能较好的保留图像的结构信息，与K-SVD和BM3D等现有的流行算法相比，具有更高的峰值信噪比（PSNR）(It firstly get the redundant dictionary of a noised image by dictionary learning.Then,the image patches are gathered according to their similarities.Meanwhile,the similar patches get sparse representation showed in dictionaries by iterative shrinkage and L1 regularization constraints and eventually the image is restored and noise is removed.The experimental results indicate that the proposed algorithm can well preserve the structure information of the common image with a higher Peak Signal to Noise Ratio(PNSR),compared with state-of-the-art algorithms,such as K-SVD and BM3D)

TV模型属于图像处理领域里面的图像修复模型，对图像处理邻域的学习有很大的裨益(The TV model belongs to the image restoration model in the field of image processing, which is of great benefit to the study of image processing neighborhoods.)

生成SAR图像程序，可以生成幅度SAR图像和强度SAR图像。(This procedure generate SAR images, and it can generate the amplitude SAR image and the intensity SAR image .)