Face-Eye-Detection

该文件包含高斯高通滤波的源代码和高斯低通滤波的源代码，可以运行，效果很好(Gaussian high-pass filter Gaussian low-pass filtering )

maximally stable extremal regions matlab codes use to detect maximally stable extremal regions.

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)

传统滤波方式如均值滤波，中值滤波，维纳滤波对图像去噪的处理以及自适应中值滤波对图像去噪。(Traditional filtering methods such as mean filtering, median filtering, wiener filtering for image denoising processing and adaptive median filter for image denoising.)

humanface detection,the programme can be used to detect human faces from the complex background!(humanface detection, the program can be used to detect human faces f rom the complex background!)

采取逆滤波和维纳滤波两种图像恢复算法对退化图像的恢复实现过程。 (taken inverse filter and two Wiener filtering algorithm to image restoration of degraded images to achieve the restoration process.)

说明：  本程序是基于小波和盒维数的车型识别程序，可以选择不同车型，有GUI界面，有图片，有程序，能运行，相信初学者一定能够获益。(This program is based on the wavelet and box dimension of the vehicle type recognition program, you can choose different models, GUI interface, pictures, programs, can run, I believe beginners will benefit.)

说明：  matlab 4个图像特征函数代码，包括tamura texture、灰度差分统计特征函数、灰度共生矩阵特征函数、灰度梯度共生矩阵特征函数(Matlab four image feature function codes, including Tamura texture, gray difference statistical feature function, gray co-occurrence matrix feature function, gray gradient co-occurrence matrix feature function)

本书详细介绍了医学图像注册方面的知识，包括配准的原理、刚性配准、非刚性配准，对于医学图像处理方面的研究具有很重要的参考价值。(The book details the registration of medical image information, including the principle of registration, rigid registration, non-rigid registration for medical image processing research has important reference value.)

由于彩色图像提供了比灰度图像更为丰富的信息, 因此彩色图像处理正受到人们越来越多的关注。彩色图像分割是彩色图像处理的重要问题, 彩色图像分割可以看成是灰度图像分割技术在各种颜色空间上的应用, 为了使该领域的研究人员对当前各种彩色图像分割方法有较全面的了解, 因此对各种彩色图像分割方法进行了系统论述, 即先对各种颜色空间进行简单介绍, 然后对直方图阈值法、特征空间聚类、基于区域的方法、边缘检测、模糊方法、神经元网络、基于物理模型方法等主要的彩色图像分割技术进行综述, 并比较了它们的优缺点, 通过比较发现模糊技术由于能很好地表达和处理不确定性问题, 因此在彩色图像分割领域会有更广阔的应用前景。(colorful image segment)