Volume 36 Issue 1
Jan.  2011
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ZHANG Qian HUANG Xin, ZHANG Liangpei, . Multiscale Image Segmentation and Classification with Supervised ECHO of High Spatial Resolution Remotely Sensed Imagery[J]. Geomatics and Information Science of Wuhan University, 2011, 36(1): 117-121.
Citation: ZHANG Qian HUANG Xin, ZHANG Liangpei, . Multiscale Image Segmentation and Classification with Supervised ECHO of High Spatial Resolution Remotely Sensed Imagery[J]. Geomatics and Information Science of Wuhan University, 2011, 36(1): 117-121.
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Multiscale Image Segmentation and Classification with Supervised ECHO of High Spatial Resolution Remotely Sensed Imagery

  • 1 State Key Laboratory of Information Engineering in Surveying,Mapping and Remote Sensing,Wuhan University,129 Luoyu Road,Wuhan 430079,China

Funds: 国家973计划资助项目(2009CB723905);国家863计划资助项目(2009AA12Z114)，国家自然科学基金资助项目(40930532,40771139,40901213)，武汉大学博士研究生自主科研基金资助项目(2008619020100061)
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  • Received Date: October 19, 2010
  • Published Date: January 04, 2011
    Graphical Abstract
    • Abstract
  • This paper presents a new method of supervised extraction and classification of homogenous object(ECHO),aiming to enhancement the multiscale homogeneity in a local neighborhood of high resolution remotely sensed imagery.This method fused multiscale spectral and spatial information using a series of homogeneous regions such as 2×2,4×4 and 8×8 window sizes.Experiment proved that the proposed method outperforms the pixelwise MLC and the single scale ECHO method,with Washington DC data set obtained by HYDICE sensor and Beijing data set obtained by QuickBird.
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