matlab图像处理

说明：  数字摄影测量中的最小二乘匹配算法，带示例图像(Feature points matching using LSTM)

在matlab环境下基于数学形态学的图像去噪，传统去噪只选用一种结构元素，去噪效果并不理想，这种去噪方法实现简单，功能强大，无论对于高斯、椒盐、维纳等噪声都去有很强的去噪效果，且算法简单。(In the matlab environment based on mathematical morphology image denoising, denoising only use traditional elements of a structure, de-noising effect is not ideal, this denoising method is simple and powerful, both for the Gaussian, salt and pepper, Wiener such noise are to have a strong denoising effect, and the algorithm is simple.)

模糊c均值聚类算法对遥感图像分类，可自己进行修改(Fuzzy c means clustering algorithm for remote sensing image classification can be modify their)

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)

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.)

进行图像的特征提取，为图像拼接做准备，matlab(Feature extraction of image)

全部都是图像处理的最新文献，与激光雷达有关，利用激光与摄像头结合，实现主动驾驶(image processing)

本文首先概述了独立成分分析与盲信号分离， 主成分分析的关系， 然后系统地介绍了该技术的基本概念和数据模型， 对现今比较流行的各种独立成分分析算法进行了剖析和总结。最后对独立成分分析的发展及应用前景作了展望(In this paper, an overview of independent component analysis and blind signal separation, principal component analysis of the relationship, and then systematically introduces the basic concept of the technology and data models for today' s more popular variety of independent component analysis algorithm is analyzed and summarized. Finally, independent component analysis of the development and application prospects are described)

使用基于词典的稀疏表示高光谱图像分类,多任务联合稀疏表示和逐步MRF优化的高光谱图像分类(Dictionary-based sparse representation hyperspectral image classification, multi-task joint sparse representation and stepwise MRF optimized hyperspectral image classification)

图像处理中的RGB颜色空间和HSI颜色空间互相转换的程序(Image processing RGB color space and the HSI color space mutual conversion process)