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October 11, 2002 11:3 Trim Size: 9.75in x 6.5in for Review Volume aksoyvisualgrammar SCENE MODELING AND IMAGE MINING WITH A
 

Summary: October 11, 2002 11:3 Trim Size: 9.75in x 6.5in for Review Volume aksoyvisualgrammar
CHAPTER 1
SCENE MODELING AND IMAGE MINING WITH A
VISUAL GRAMMAR
Selim Aksoy, Carsten Tusk, Krzysztof Koperski, Giovanni Marchisio
Insightful Corporation
1700 Westlake Ave. N., Suite 500, Seattle, WA 98109, USA
E-mail: {saksoy,ctusk,krisk,giovanni}@insightful.com
Automatic content extraction, classification and content-based retrieval are highly
desired goals in intelligent remote sensing databases. Pixel level processing has
been the common choice for both academic and commercial systems. We extend
the modeling of remotely sensed imagery to three levels: Pixel level, region level
and scene level. Pixel level features are generated using unsupervised clustering of
spectral values, texture features and ancillary data like digital elevation models.
Region level features include shape information and statistics of pixel level feature
values. Scene level features include statistics and spatial relationships of regions.
This chapter describes our work on developing a probabilistic visual grammar
to reduce the gap between low-level features and high-level user semantics, and
to support complex query scenarios that consist of many regions with different
feature characteristics. The visual grammar includes automatic identification of

  

Source: Aksoy, Selim - Department of Computer Engineering, Bilkent University

 

Collections: Computer Technologies and Information Sciences