deeplab_v3-master

区域生长法获取图像边界 必须有种子 可以有很多方法 这里直接鼠标点击(Region growing method to obtain the image the border must have a lot of methods of seed can have a direct mouse click here)

radon 的逆变换,可以实现图像重建，前提是前面的投影用radon变换来做(iradon)

用于图像去噪的代码，有模型去噪、双树复小波去噪，希望有帮助。(Code for image denoising, a denoising model dual tree complex wavelet denoising, hope to have help。)

本程序集合了互信息配准，PV差值，powell算法，基于小波变换的图像融合的一整套算法。只需要在GUI界面输入两幅图像，即可自动完成图像的配准融合。程序包含Matlab源代码。用Matlab打开imagefusion.m，即会弹出gui界面。融合前要输入参考和浮动图像。图像要求像素的 长＊宽 一样。否则会报错。程序只能处理灰度图像，彩色图像也会转化成灰度图像处理。程序代码已经有详细的注释，方便读者理解。(The procedures set of mutual information, PV difference, powell algorithm, based on wavelet transform image fusion set of algorithms. Only need to enter the two images in the GUI interface, you can automatically complete the image registration fusion. Program contains Matlab source code. Using Matlab open imagefusion.m, gui interface will pop up. Fusion before the input reference and floating images. Image requires the same pixel length* width. Otherwise incorrect. Can only handle grayscale images, color images into gray image processing also. Program code has detailed notes, to facilitate understanding.)

分形图像压缩 效果好 但是运行时间长 需要改进(Fractal image compression effective running a long time but need to improve)

说明：  另外一种有效的椭圆陪陪技术，对于亚像素边缘检测非常有用的，真的不错(Oval to chat with another kind of effective techniques for sub-pixel edge detection is very useful, really good)

基于先验信息和射影几何变换的车牌图像矫正 对于图像矫正还是有帮助的(License plate image correction based on a priori information and projective geometry transform for image correction or help)

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. )

detect face and recognition with lpd and pca

SIFT 尺度不变特征提取算法 可参考可运行有测试图片(SIFT with test picture and it can work well)