高光谱遥感数据在地物分类中的应用.docVIP

本科学生毕业论文 高光谱遥感数据在地物分类中的应用 黑 龙 江 工 程 学 院 二○一二年六月 The Graduation Thesis for Bachelors Degree Hyperspectral Remote Sensing Data In Terrain Classification Application 摘 要 高光谱图像的高分辨率、多波段数、窄波段宽度、大数据量在为人类带来巨大的研究价值的同时，也给高光谱图像的处理带来了巨大的挑战。分类方法在其研究中占有重要的地位，方法的优劣直接关系着分类的精度。本文阐述了遥感基本理论和图像预处理的一些方法，简要概述了遥感图像分类的概念和原理，详细探讨了传统的遥感分类方法——监督分类和非监督分类，以及近年来出现的一些较新的分类方法，对各种方法的原理，算法及各自的优缺点进行了比较分析。 总之，遥感影像的监督分类和非监督分类方法，是影像分类的最基本、最概括的两种方法。传统的监督分类和非监督分类方法虽然各有优势，但是也都存在一定的不足。而新的分类方法如神经网络以其自适应、自学习、联想记忆和分布存储等良好特性，被人们加以重视和广泛应用于图像分类中，打破了传统的统计分类方法的局限，提高了分类速度和精度。虽然各种分类方法各有特点，但在实际工作中还需要综合应用多种分类方法，以提高分类的准确率与精度。 关键词：图像分类；监督分类；非监督分类；高光谱 ABSTRACT Higher spectral resolution，more of channels，narrower bandwidth and larger amount of data of hyperspectral image not only bring great research values for human being，but also bring larger challenges for Processing them．Classification，in its study，which occupies all important position，the merits directly related to the classification accuracy．This paper explain the basic theory and remote sensing image preprocessing of the ways，a brief overview of the remote sensing image classification concepts and principles．detailed study of the traditional classification of remote sensing methods—supervised and unsupervised classification，and the emergence of some relatively new classification in recent years. Compared with the various methods of principle，algorithms and their respective advantages and disadvantages．Finally，the use of different remote sensing classification of the actual image classification，the classification analysis，come to different methods used in the actual process characteristics． In short，remote sensing image classification of supervision and non-supervised classification method are the most basic and general method in image classification. Traditional supervised and unsupervised classification despite their different strengths，but there is some deficiency．And the new classification methods such as neural networks with adaptive，self-learning，ass