TY - GEN
T1 - A fuzzy inference system for multispectral image classification
AU - Vega, Pedro J.Soto
AU - Quirita, Victor A.Ayma
AU - Achanccaray, Pedro M.
AU - Tanscheit, Ricardo
AU - Vellasco, Marley
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2017/1/27
Y1 - 2017/1/27
N2 - This work presents an approach for multispectral image classification that makes use of a Fuzzy Inference System (FIS). An IKONOS satellite sensor image of a neighborhood in Rio de Janeiro, Brazil has been used. The ground truth used in this work comprises six classes: trees, scrub, buildings, roads, water and shadows. Then, inputs sets, rules and outputs sets were defined. Four input variables, based on four indexes computed from the image spectral bands, have been considered: Normalized Difference Vegetation Index (NDVI), Buildings Index (BI), Water Index (WI) and Road Index (RI). Experimental results show that the proposed method outperforms other methods, achieving higher Overall and Average accuracies, providing a better representation of the classification process.
AB - This work presents an approach for multispectral image classification that makes use of a Fuzzy Inference System (FIS). An IKONOS satellite sensor image of a neighborhood in Rio de Janeiro, Brazil has been used. The ground truth used in this work comprises six classes: trees, scrub, buildings, roads, water and shadows. Then, inputs sets, rules and outputs sets were defined. Four input variables, based on four indexes computed from the image spectral bands, have been considered: Normalized Difference Vegetation Index (NDVI), Buildings Index (BI), Water Index (WI) and Road Index (RI). Experimental results show that the proposed method outperforms other methods, achieving higher Overall and Average accuracies, providing a better representation of the classification process.
KW - fuzzy inference systems
KW - image processing
KW - multispectral image classification
KW - remote sensing
UR - http://www.scopus.com/inward/record.url?scp=85015200405&partnerID=8YFLogxK
U2 - 10.1109/ANDESCON.2016.7836268
DO - 10.1109/ANDESCON.2016.7836268
M3 - Conference contribution
AN - SCOPUS:85015200405
T3 - Proceedings of the 2016 IEEE ANDESCON, ANDESCON 2016
BT - Proceedings of the 2016 IEEE ANDESCON, ANDESCON 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2016 IEEE ANDESCON, ANDESCON 2016
Y2 - 19 October 2016 through 21 October 2016
ER -