FUSION OF GENETIC-PROGRAMMING-BASED INDICES IN HYPERSPECTRAL IMAGE CLASSIFICATION TASKS

Autor(es)

Hernandez Albarracin, Juan F. ; Ferreira, Edemir, Jr. ; dos Santos, Jefersson A. ; Torres, Ricardo da S. ; IEEE

• Tipo de documento: Artigo Científico
• Fonte: 2017 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS); v. N/A, p. 4-pg., 2017-01-01.

Resumo

This paper introduces a two-step hyper- and multi-spectral image classification approach. The first step relies on the use of a genetic programming (GP) framework to both select and combine appropriate bands. The second step is concerned with the image classification itself. We present two strategies for multi-class classification problems based on the combination of GP-based indices defined in binary classification scenarios. Performed experiments involving well-known and widely-used datasets demonstrate that the proposed approach yields comparable or better effectiveness performance when compared to several traditional baselines. (AU)

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