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改进的图像分割算法：运用SLIC超像素分割和DBSCAN聚类算法相结合的方法实现图像分割(Image Segmentation using SLIC SuperPixels and DBSCAN Clustering)

说明：  将girl 图像进行分割，达到2*4的图像分割结果。并使用tight_subplot函数将分割间距变小。(The girl image is segmented to achieve a 2*4 image segmentation result. And use the tight_subplot function to make the division interval smaller.)

自适应直方图均衡算法的实现，即AHE算法，并提供样图进行对比。(Adaptive histogram equalization algorithm to achieve, namely AHE algorithm and provide comp image comparison.)

基于区域增长对图像进行分割，得到感兴趣区域(Sengment image based on the regiongrowing.)

滤波器图像增强的matlab算法实现程序。本人自己给出的程序代码(gabor wavelet matlab algorithm. Program code given by the original author)

用来读写高光谱遥感影像的matlab代码，支持BSQ,BIL,BIP格式，三种文件格式对应的是头文件*.lxw中的第5个数字，头文件可用写字板编辑(The matlab code used to read and write in Hyperspectral Imagery support BSQ, BIL, BIP, format, corresponding to three types of file formats is a header file*. Lxw in the first five digits, the first file available WordPad editor)

说明：  图像滤波模型,可用于图像滤波，效果良好，模型特别简单。(The image filtering model can be used for image filtering. The effect is good, and the model is particularly simple.)

guided_filter滤波器。对于图像处理方面有用。(filter. It is useful for image processing.)

基于核函数的FCM算法在医学图像分割上的应用(The application of FCM algorithm based on kernel function in medical image segmentation)

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. )