The Methods of Image Segmentation on Application and Analysis of Remote Sensing Images

Abstract

Image segmentation is the basis of pattern recognition and the first step for extracting the objects automatically from image using computer.This is significant for the application and analysis of remote sensing images.These years,with an increasing amount of high resolution imagery of high quality provided,some effective segmentation methods are required for the related geoscience applications of high resolution images.However,for the unique characteristics of high resolution image,classic image segmentation methods cannot be satisfied.The methods for segmentation using in the application and analysis of remote sensing images are overviewed and analyzed.Considering the characteristics of high resolution image,the technical difficulties of segmentation for high resolution remote sensing image are analyzed,and the problems of the traditional pixel-based methods are given.Afterward,mathematic morphology method,OOA(Object Oriented Analysis) and some other methods are illustrated.These methods,which have more advantages for high resolution image segmentation,can make good use of the objects' attributes such as tone,texture and geometry.Finally,the future development of image segmentation technology using in application and analysis of remote sensing images is put forward.