pcadenoise

基于IDL的HJ_1A 高光谱HSI图像条带噪声去除方案研究(Based the IDL' s HJ_1A hyperspectral HSI image strips with noise removal solutions for research)

实现了20000*20000以上的大tiff格式遥感图像的读写和显示，用于遥感图像处理(Achieve a 20,000* 20,000 or more large remote sensing image tiff format to read and write and display for remote sensing image processing)

阈值重心法实现光带中心线提取，可用于结构光扫描的模型建立，处理二值化图像等。(Threshold barycenter method is used to extract the center line of optical band. It can be used to model structured light scanning and process binary images.)

说明：  用matlab写的分水岭算法用于图像分割写的不是很好有需要的看看吧(using Matlab was a watershed for image segmentation algorithm was not very good in need and let's see it)

本程序对梯度-灰度共生矩阵进行求解，并对其进行归一化的处理。(Gradient of the program- to solve GLCM, and its normalization processing.)

说明：  图像频域处理 CT技术与图像的重建 通过一维投影复原二维图像 Matlab实现 (Frequency domain image processing and image reconstruction of CT one-dimensional projection by Matlab to achieve two-dimensional image restoration)

说明：  一、主要研究内容 1.基本内容 本设计目标在于利用Matlab强大的图像处理能力和实用便捷的编程方法，通过处理包含人脸的视频帧系列图像，灰度积分投影技术的眼睛定位方法，进而利用perclos计数，计算眨眼率，从而得到比较准确的疲劳状况。包括lun文初稿撰写。 2.具体要求 本设计基于灰度积分投影技术的眼睛定位方法，再结合perclos技术。首先通过图像预处理技术得到灰度分配较为均匀的图像,然后分别利用水平和垂直灰度积分投影曲线结合人脸的结构特征找到眼睛的位置坐标,实现了准确的眼睛定位,通过perclos技术技术眨眼率，根据先验值得到是否疲劳。 二、算法原理 视频输入——预处理去除非人脸区域——人脸定位——人眼定位（灰度积分投影）——眼睛张合度——perclos技术统计——输出结果 三、GUI界面设计 [需要有一定编程功底](1. Basic contents The goal of this design is to use the powerful image processing ability of MATLAB and the practical and convenient programming method, through processing the video frame series images including face, the eye location method of gray integral projection technology, and then using PERCLOS count to calculate the blink rate, so as to get a more accurate fatigue condition. Including the first draft of Lun.)

说明：  无人机影像ORB特征提取和RANSAC算法剔除(UAV image ORB feature extraction and RANSAC algorithm elimination)

利用sift算法提取两张图像的特征点，利用ransac去除误匹配，最后将两张图片拼接在一起(Using sift algorithm to extract the two feature points of the image, the use of ransac to remove the wrong match, and finally the two pictures together)

说明：  模式识别与图像处理，图像的边缘处理，增强(Pattern recognition and image processing, image edge processing, to enhance)