Image-Based Airborne Sensors: A Combined Approach for Spectral Signatures Classification through Deterministic Simulated Annealing

Sensors

Mar໚ Guijarro²  Gonzalo Pajares¹ 

[1] Departamento de Ingeniería del Software e Inteligencia Artificial, Facultad Informática, Universidad Complutense, 28040 Madrid, Spain; E-Mail:;Ingeniería Técnica en Informática de Sistemas, Centro Superior de Estudios Felipe II, 28300 Aranjuez, Madrid, Spain

关键词: deterministic simulated annealing;    image-based airborne sensors;    classifier combination;    fuzzy classifier;    Bayesian classifier;    unsupervised;    spectral signatures classification;   

DOI  :  10.3390/s90907132

来源: mdpi

【 摘 要 】

The increasing technology of high-resolution image airborne sensors, including those on board Unmanned Aerial Vehicles, demands automatic solutions for processing, either on-line or off-line, the huge amountds of image data sensed during the flights. The classification of natural spectral signatures in images is one potential application. The actual tendency in classification is oriented towards the combination of simple classifiers. In this paper we propose a combined strategy based on the Deterministic Simulated Annealing (DSA) framework. The simple classifiers used are the well tested supervised parametric Bayesian estimator and the Fuzzy Clustering. The DSA is an optimization approach, which minimizes an energy function. The main contribution of DSA is its ability to avoid local minima during the optimization process thanks to the annealing scheme. It outperforms simple classifiers used for the combination and some combined strategies, including a scheme based on the fuzzy cognitive maps and an optimization approach based on the Hopfield neural network paradigm.

【 授权许可】

CC BY   
© 2009 by the authors; licensee MDPI, Basel, Switzerland