snakedemo

关于图像配准的经典外文文献，影响因子很高(on the registration of foreign classic literature, high impact factor)

对两幅图像提取特征点，并计算基本矩阵，对两幅图像进行极线矫正，并画出校正后图像特征点的极线，效果非常好(The two images of the image feature points in the feature points are extracted, and the calculated fundamental matrix, correction of lines of the two images, and after the draw correction lines, very good results)

将dct生成的8*8块图像数据进行zigzag排序，以及恢复算法，在脆弱水印中使用。(The program zigzag sort 8*8 image data generated by dct, and restore algorithm, which is used in fragile watermarking.)

增强图像中的有用信息，它可以是一个失真的过程，其目的是要改善图像的视觉效果，针对给定图像的应用场合(Enhance the useful information in the image, it can be a process of distortion, its purpose is to improve image visual effect, for a given image)

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)

说明：  通过高斯、指数、瑞利、gamma、pearson、weibull模型分别对同质区域的SAR图像的强度分布进行拟合(The intensity distributions of SAR images in homogeneous regions are fitted by Gauss, exponential, Rayleigh, gamma, Pearson and Weibull models respectively.)

详细说明：几个关于图像灰度变换的程序。包括图像反色，图像的对数灰度变换，指数灰度变换，线性灰度变换，灰度切割，图像平均降噪。 (Several of the image gray-scale transformation process. Including anti-color image, the image of the number of gray level transformation, index gray-scale transformation, linear gray level transformation, gray cut, the average image noise.)

说明：  jm软件源码，用于流媒体编码标准H264的性能评测(jm-source software for streaming media encoding standard of the performance evaluation H264)

本书是计算机视觉编程的权威实践指南,依赖 Python 语言讲解了基础理论与算法,并通过 大量示例细致分析了对象识别、基于内容的图像搜索、光学字符识别、光流法、跟踪、三维重建、 立体成像、增强现实、姿态估计、全景创建、图像分割、降噪、图像分组等技术。(This book is an authoritative guide to computer vision programming, which explains basic theories and algorithms based on the Python language.A large number of examples carefully analyze object recognition, content based image search, optical character recognition, optical flow, tracking, 3D reconstruction,Stereoscopic imaging, augmented reality, attitude estimation, panoramic creation, image segmentation, noise reduction, image grouping and other techniques.)

说明：  本代码使用MATLAB编写的基于GST模型的红外弱小目标检测代码(% This source code is for infrared small target detection method based on Generalized Structure Tensor (GST). % If you use this code in your publications, please cite:)