Information mining in remote sensing image archives: System concepts

被引：160

作者：

Datcu, M ^{[1
]}

Daschiel, H

Pelizzari, A

Quartulli, M

Galoppo, A

Colapicchioni, A

Pastori, M

Seidel, K

Marchetti, PG

D'Elia, S

机构：

[1] Remote Sensing Technol Inst, German Aerosp Ctr, DLR, D-82234 Oberpfaffenhofen, Germany

[2] Appunto Solucoes Informat Lda, P-1000112 Lisbon, Portugal

[3] Adv Comp Syst SpA, ACS, Earth Observat Div, I-00139 Rome, Italy

[4] Swiss Fed Inst Technol, ETH, Comp Vis Lab, CH-8092 Zurich, Switzerland

[5] European Space Agcy, Directorate Earth Observ Programmes, Earth Observat Applicat Dept, ESRIN, I-00044 Frascati, Italy

来源：

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING | 2003年 / 41卷 / 12期

关键词：

content-based image retrieval (CBIR); image information mining; information extraction; statistical learning;

D O I：

10.1109/TGRS.2003.817197

中图分类号：

P3 [地球物理学]; P59 [地球化学];

学科分类号：

0708 ; 070902 ;

摘要：

In this paper, we demonstrate the concepts of a prototype of a knowledge-driven content-based information mining system produced to manage and explore large volumes of remote sensing image data. The system consists of a computationally intensive offline part and an online interface. The offline part aims at the extraction of primitive image features, their compression, and data reduction, the generation of a completely unsupervised image content-index, and the ingestion of the catalogue entry in the database management system. Then, the user's interests-semantic interpretations of the image content-are linked with Bayesian networks to the content-index. Since this calculation is only based on a few training samples, the link can be computed online, and the complete image archive can be searched for images that contain the defined cover type. Practical applications exemplified with different remote sensing datasets show the potential of the system.

引用

页码：2923 / 2936

页数：14

共 18 条

[1]

[Anonymous], P IEEE INT GEOSC REM

[2]

[Anonymous], ACM MULTIMEDIA

[3]

[Anonymous], 2001, BAYESIAN THEORY

[4]

BACH J, 1996, P SPIE C STOR RETR I, P76

[5] Titan: A high-performance remote-sensing database [J].

Chang, CL ;

Moon, B ;

Acharya, A ;

Shock, C ;

Sussman, A ;

Saltz, J .

13TH INTERNATIONAL CONFERENCE ON DATA ENGINEERING - PROCEEDINGS, 1997, :375-384

[6]

COX IJ, 1996, P INT C PATT REC VIE, V3, P361

[7]

DASCHIEL H, 2002, P SPIE REM SENS S

[8] Spatial information retrieval from remote-sensing images - Part 1: Information theoretical perspective [J].

Datcu, M ;

Seidel, K ;

Walessa, M .

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 1998, 36 (05) :1431-1445

[9]

DATCU M, 2002, P 4 EUR C SYNTH AP R

[10]

FLICKNER M, 1995, IEEE COMPUT, V28, P23, DOI DOI 10.1109/2.410146

← 1 2 →