EVALUATION OF SATELLITE IMAGE SEGMENTATION USING SYNTHETIC IMAGES

被引：4

作者：

Marcal, Andre R. S. ^{[1
]}

Rodrigues, Arlete ^{[1
]}

Cunha, Mario ^{[1
]}

机构：

[1] Univ Porto, Ctr Invest Ciencias Geoespaciais, Fac Ciencias, Oporto, Portugal

来源：

2010 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM | 2010年

关键词：

Image processing; Image segmentation;

D O I：

10.1109/IGARSS.2010.5649930

中图分类号：

P [天文学、地球科学];

学科分类号：

07 ;

摘要：

The segmentation stage is a key aspect of an object-based image analysis system. However, the segmentation quality is usually difficult to evaluate for satellite images. The Synthetic Image TEsting Framework (SITEF) is a tool to evaluate and compare image segmentation results. This paper presents an example of the use of SITEF for the evaluation of a segmentation algorithm, using a SPOT HRG satellite image with 6 vegetation land cover classes identified in an agricultural area. The segmentation results were evaluated under various perspectives, including the parcel size and shape, the land cover types, and the parameters used in the segmentation algorithm.

引用

页码：2210 / 2213

页数：4

共 8 条

[1] Assessment of very high spatial resolution satellite image segmentations [J].

Carleer, AP ;

Debeir, O ;

Wolff, E .

PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING, 2005, 71 (11) :1285-1294

[2]

*DEFINIENS, 2008, DEF DEV 7 US GUID

[3]

HAMMOUDE A, 1998, THESIS U WASHINGTON

[4] An automated object-based approach for the multiscale image segmentation of forest scenes [J].

Hay, GJ ;

Castilla, G ;

Wulder, MA ;

Ruiz, JR .

INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2005, 7 (04) :339-359

[5]

Marcal A. R. S., 2009, IEEE IGARSS 2009, VIV, P236

[6] A method for multi-spectral image segmentation evaluation based on synthetic images [J].

Marcal, Andre R. S. ;

Rodrigues, Arlete S. .

COMPUTERS & GEOSCIENCES, 2009, 35 (08) :1574-1581

[7]

Neubert M., 2008, OBJECT BASED IMAGE A, P769, DOI [10.1007/9783-54077058-942, DOI 10.1007/978-3-540-77058-9_42, 10.1007/978-3-540-77058-9_42]

[8] Classification of multisource remote sensing imagery using a Genetic Algorithm and Markov random fields [J].

Tso, BCK ;

Mather, PM .

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 1999, 37 (03) :1255-1260

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