测绘科学技术学报2017，Vol.34Issue(5)：486-490,5.DOI:10.3969/j.issn.1673-6338.2017.05.010
HSV变换和多尺度分割相结合的高分辨率遥感影像阴影检测
Shadow Detection from High Resolution Remote Sensing Imagery Based on HSV Transformation and Multilevel Segmentation
摘要
Abstract
According to the shadow characteristics in high resolution remote sensing imagery,a method based on color space transformation and multilevel segmentation is proposed in this paper.Firstly,the value and hue of the original image are extracted respectively by two consecutive HSV transformation.Then,object-oriented analysis is used for multi-scale segmentation and shadow detection in single scale.Finally,the ultimate extraction is accomplished by decision level fusion.The presented method is evaluated with GF-2 and Google Earth imageries.The results show that the proposed shadow detection algorithm can combine the advantages of different scales and has a performance in terms of a low errors and leakages and great recognition to the partial shadow and dark object.关键词
高分辨率遥感影像/阴影检测/面向对象/多尺度分割/决策级融合Key words
high resolution remote sensing imagery/shadow detection/object-oriented method/multilevel segmentation/decision level fusion分类
天文与地球科学引用本文复制引用
林雨准,张保明,郭海涛,王丹菂,秦宇..HSV变换和多尺度分割相结合的高分辨率遥感影像阴影检测[J].测绘科学技术学报,2017,34(5):486-490,5.基金项目
国家自然科学基金项目(41601507) （41601507）
地理信息工程国家重点实验室开放基金项目(SKLGIE 2015-M-3-3). （SKLGIE 2015-M-3-3）
