张倩, 黄昕, 张良培. 多尺度同质区域提取的高分辨率遥感影像分类研究[J]. 武汉大学学报 ( 信息科学版), 2011, 36(1): 117-121.
引用本文: 张倩, 黄昕, 张良培. 多尺度同质区域提取的高分辨率遥感影像分类研究[J]. 武汉大学学报 ( 信息科学版), 2011, 36(1): 117-121.
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.

多尺度同质区域提取的高分辨率遥感影像分类研究

Multiscale Image Segmentation and Classification with Supervised ECHO of High Spatial Resolution Remotely Sensed Imagery

  • 摘要: 提出了一种监督的多尺度同质区域的提取、融合和分类方法(ECHO),该方法同时考虑了地物的光谱。和空间信息。利用空间分辨率为5 m的华盛顿商业街数据和空间分辨率为0.7 m的北京地区QuickBird数据,证明该方法能有效提高高分辨率遥感影像的解译精度。

     

    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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