Pyramidal contextual classification of SAR images

Author

Bénié, Goze B. ; Boucher, Jean-Marc ; Plehiers, Stéphane ; Massalabi, Amani ; Wang, Shengrui

Author_Institution

GRAIN, Sherbrooke Univ., Que., Canada

Volume

2

fYear

34881

fDate

10-14 Jul1995

Firstpage

913

Abstract

Pyramid-based classification techniques have shown great performance when compared to global classification methods. However, the accuracy becomes very low when spectral parameters only are considered. A new classification method is proposed which deals with integration of two algorithms: the hierarchical image segmentation by step-wise optimization to take into account the spatial context, and the Iterative Conditional Mode algorithm to classify the segmented image. After a comprehensive description of the new algorithm, its performance is analysed with SAR agricultural data

Keywords

agriculture; geophysical signal processing; geophysical techniques; image classification; image segmentation; iterative methods; radar applications; radar imaging; remote sensing by radar; spaceborne radar; synthetic aperture radar; Iterative Conditional Mode algorithm; SAR image; algorithm; context; crops agriculture; farmland; geophysical measurement technique; hierarchical image segmentation; image classification; land surface; pyramidal contextual classification; radar remote sensing; step-wise optimization; terrain mapping; Algorithm design and analysis; Classification algorithms; Costs; Data mining; Image segmentation; Iterative algorithms; Iterative methods; Merging; Optimization methods; Partitioning algorithms; Performance analysis; Remote sensing; Telephony;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium, 1995. IGARSS '95. 'Quantitative Remote Sensing for Science and Applications', International

Conference_Location

Firenze

Print_ISBN

0-7803-2567-2

Type

conf

DOI

10.1109/IGARSS.1995.521095

Filename

521095