Paper
28 January 2002 Misclassification correction in primary local recognition of component images of multichannel remote sensing data
Antti Niemistoe, Vladimir V. Lukin, Alexander N. Dolia, Olli P. Yli-Harja, Ilya Shmulevich
Author Affiliations +
Proceedings Volume 4541, Image and Signal Processing for Remote Sensing VII; (2002) https://doi.org/10.1117/12.454147
Event: International Symposium on Remote Sensing, 2001, Toulouse, France
Abstract
We propose an automatic classification procedure for multichannel remote sensing data. The method consists of several stages. An important stage is the correction of misclassifications based on the use of a nonlinear graph-based estimation technique recently introduced by us. The misclassification correction method is optimized by means of a training-based framework using genetic algorithms. It is shown that this provides a considerable improvement in classification accuracy. After primary local recognition and misclassification correction of all component images, an approach to further use the obtained data is considered. At this joint classification stage we introduce novel subclasses like 'common homogeneous region, common edge, small sized object in one or two components, etc. Numerical simulation data as well as real image processing results are presented to confirm the basic steps of remote sensing data classification and the efficiency of the proposed approach.
© (2002) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Antti Niemistoe, Vladimir V. Lukin, Alexander N. Dolia, Olli P. Yli-Harja, and Ilya Shmulevich "Misclassification correction in primary local recognition of component images of multichannel remote sensing data", Proc. SPIE 4541, Image and Signal Processing for Remote Sensing VII, (28 January 2002); https://doi.org/10.1117/12.454147
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Cited by 4 scholarly publications.
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KEYWORDS
Image classification

Remote sensing

Radar

Image processing

Genetic algorithms

Optimization (mathematics)

Data modeling

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