文章基本信息

标题：AUTOMATED TECHNIQUES FOR SATELLITE IMAGE SEGMENTATION
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作者：Alberto Guarnieri ; Antonio Vettore
期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2002
卷号：XXXIV Part 4
出版社：Copernicus Publications
摘要：In this paper a combined method between "classical" and automatic approach for remote sensing image analysis is presented. Typically, satellite images are used in order to detect the distribution of vegetation, soil classes, built-up areas, roads, and water body as rivers, brooks, lakes, ecc. Referring for example to Landsat-TM images, the identification of such aspects is performed through the "classical" approach of image classification. Basically, it deals with the use of pseudocolors and/or combinations of various spectral bands to acquire different thematic layers from the images. In this work a further processing step is introduced, namely a segmentation algorithm is applied to color images in order to improve the image analysis both from qualitative and quantitative point of view. This algorithm belongs to the class of operations performed in the automatized unsupervised analysis of color images. Last recent advances in the field of computer science and CPU performance have lead to a great reduction of data processing times, allowing therefore to apply also in the field of Remote Sensing more complex algorithms. The proposed segmentation algorithm is based on a feature-space approach and implements two processing techniques: the "histogram thresholding" [1] and the "clustering" [2]. Some interesting results applied to Remote Sensing images will be provided
关键词：satellite image classification; image segmentation; clustering