matlab-phase-unwrapping

遥感影像处理，可以用于盲源信号分离，快速高效的独立成分分析方法(Remote sensing image processing, can be used for blind source separation, rapid and efficient method of independent component analysis)

采用最小交叉熵，最大熵，OTSU阈值分割(Using minimum cross entropy, maximum entropy, OTSU thresholding)

说明：  HU的七个不变矩，每个文件是一个子程序，对应冈萨雷斯的数字图像处理教程的(HU)

说明：  实现多个阈值的图像分割及K-mean聚类的图像分割(Multiple threshold image segmentation or K-mean clustering image segmentation)

本书主要讨论了图像的各类矩函数（几何矩、复数矩、Legendre矩、Zernike矩、小波矩等）的定义、性质和快速算法，以及它们的不变量函数。并就它在图像处理和识别，计算机视觉以及其它方面的应用作了必要的介绍。 (This book discusses the various types of image moment function (geometric moments, complex moments, Legendre moments, Zernike moments, wavelet moment, etc.) of the definition, nature and fast algorithm, and their non-variable function. On it in the image processing and recognition, computer vision, and other aspects of the application made the necessary introduction.)

说明：  四种算子(sobel,prewitt,roberts,marr)进行图像边缘检测的matlab源码.(Operators of four (sobel, prewitt, roberts, marr) image edge detection matlab source.)

灰度差分统计法提取图像纹理特征，包括平均值，对比度，熵，等特征，matlab函数，直接接使用，无需修改，中文注释，通俗易懂(Gray difference statistical method is used to extract texture features of image, including mean value, contrast, entropy, etc., matlab function, directly used without modification, Chinese annotation, and easy to understand)

对BMP文件进行图像处理，包括：边缘检测、频域变换、几何变换、图像变换校正、灰度变换、图像编码、平滑和匹配(BMP files for image processing, comprising: an edge detection, a frequency domain transformation, geometric transformation, image transformation correction gradation conversion, image coding, and matching the smooth)

图像分割源程序 通过融合处理，％ image segmentation based on multispectral image fusion ％ and morphology reconstruction watershed ％ main program (image segmentation source through fusion, % image segmentation based on multispectral im age fusion% and morphology reconstruction wat ershed% main program)

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. )