Spatial resolution limits in extraction of BRDF feature from remote sensing image data

被引:0
|
作者
Liu, Q [1 ]
Liu, QH [1 ]
Menenti, M [1 ]
机构
[1] Chinese Acad Sci, IRSA, Lab Remote Sensing Informat Sci, Beijing, Peoples R China
关键词
BRDF; multiangular remote sensing;
D O I
暂无
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
In the process of applying the theoretic results of BRDF model study to remote sensing image data, an important step is to extract BRDF features from multi-angular images. Because of the limitations of registration, pixel alignment and the intrinsic scale of scene, it is necessary to perform spatial average to the georeferenced multi-angular images before extracting BRDF feature. Otherwise the feature will not be representative to the surface property. Based on analysis of geometrical limitations, this paper discussed how the apparent BRDF feature changes from random to order after the spatial average.
引用
收藏
页码:726 / 728
页数:3
相关论文
共 50 条
  • [1] Spectral and spatial feature integrated method for edge information extraction from high resolution remote sensing image
    Li, QQ
    Ma, JW
    Hasibagan
    Han, XZ
    Liu, ZL
    [J]. IGARSS 2003: IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS I - VII, PROCEEDINGS: LEARNING FROM EARTH'S SHAPES AND SIZES, 2003, : 2945 - 2947
  • [2] Spectral and spatial feature integrated edge extraction method for high resolution remote sensing image
    Li, QQ
    Ma, JW
    Bagan, H
    Han, XZ
    Liu, ZL
    [J]. THIRD INTERNATIONAL SYMPOSIUM ON MULTISPECTRAL IMAGE PROCESSING AND PATTERN RECOGNITION, PTS 1 AND 2, 2003, 5286 : 823 - 826
  • [3] The extraction of plantation with texture feature in high resolution remote sensing image
    Chen, Gong
    Liang, Shouzhen
    Chen, Jingsong
    [J]. 2014 THIRD INTERNATIONAL WORKSHOP ON EARTH OBSERVATION AND REMOTE SENSING APPLICATIONS (EORSA 2014), 2014,
  • [4] A New Method for Spatial Feature Extraction and Classification of Remote Sensing Image
    Zhang, Xi
    Zhang, Shuyi
    Xu, Jiangfeng
    Wang, Jinfei
    [J]. 2006 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-8, 2006, : 2727 - +
  • [5] On the classification of remote sensing high spatial resolution image data
    Batista, Marlos Henrique
    Haertel, Victor
    [J]. INTERNATIONAL JOURNAL OF REMOTE SENSING, 2010, 31 (20) : 5533 - 5548
  • [6] Feature extraction in remote sensing high-dimensional image data
    Zortea, Maciel
    Haertel, Victor
    Clarke, Robin
    [J]. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2007, 4 (01) : 107 - 111
  • [7] DIFET: DISTRIBUTED FEATURE EXTRACTION TOOL FOR HIGH SPATIAL RESOLUTION REMOTE SENSING IMAGES
    Eken, S.
    Aydin, E.
    Sayar, A.
    [J]. 4TH INTERNATIONAL GEOADVANCES WORKSHOP - GEOADVANCES 2017: ISPRS WORKSHOP ON MULTI-DIMENSIONAL & MULTI-SCALE SPATIAL DATA MODELING, 2017, 4-4 (W4): : 209 - 213
  • [8] Road Extraction From a High Spatial Resolution Remote Sensing Image Based on Richer Convolutional Features
    Hong, Zhaoli
    Ming, Dongping
    Zhou, Keqi
    Guo, Ya
    Lu, Tingting
    [J]. IEEE ACCESS, 2018, 6 : 46988 - 47000
  • [9] ROAD CENTERLINES EXTRACTION FROM HIGH RESOLUTION REMOTE SENSING IMAGE
    Sun, Shikai
    Xia, Wei
    Zhang, Bingqi
    Zhang, Ying
    [J]. 2019 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2019), 2019, : 3931 - 3934
  • [10] A Multimodal Feature Fusion Network for Building Extraction With Very High-Resolution Remote Sensing Image and LiDAR Data
    Luo, Hui
    Feng, Xibo
    Du, Bo
    Zhang, Yuxiang
    [J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2024, 62