A fuzzy hyperspectral classi®er for automatic target recognition (ATR) systems
نویسندگان
چکیده
In this paper we present a fuzzy system based hyperspectral classi®er for automatic target identi®cation. The system is based on partitioning the spectral band space into clusters using a modi®ed fuzzy C-Means clustering algorithm. Classi®cation of each pixel is then carried out by calculating its fuzzy membership in each cluster. The results showed that the fuzzy hyperspectral classi®er is successful in target identi®cation using materials spectrum. Also it provides a fuzzy identi®cation value that can be used later on in the decision-making stage of automatic target recognition (ATR) systems. Ó 1999 Elsevier Science B.V. All rights reserved.
منابع مشابه
A fuzzy hyperspectral classifier for automatic target recognition (ATR) systems
In this paper we present a fuzzy system based hyperspectral classi®er for automatic target identi®cation. The system is based on partitioning the spectral band space into clusters using a modi®ed fuzzy C-Means clustering algorithm. Classi®cation of each pixel is then carried out by calculating its fuzzy membership in each cluster. The results showed that the fuzzy hyperspectral classi®er is suc...
متن کاملUrban Vegetation Recognition Based on the Decision Level Fusion of Hyperspectral and Lidar Data
Introduction: Information about vegetation cover and their health has always been interesting to ecologists due to its importance in terms of habitat, energy production and other important characteristics of plants on the earth planet. Nowadays, developments in remote sensing technologies caused more remotely sensed data accessible to researchers. The combination of these data improves the obje...
متن کاملAutomatic Spectral Target Recognition in Hyperspectral Imagery
Automatic target recognition (ATR) in hyperspectral imagery is a challenging problem due to recent advances of remote sensing instruments which have significantly improved sensor’s spectral resolution. As a result, small and subtle targets can be uncovered and extracted from image scenes, which may not be identified by prior knowledge. In particular, when target size is smaller than pixel resol...
متن کاملSupport Vector Learning for Fuzzy Rule - Based Classi cation Systems
|To design a fuzzy rule-based classi cation system (fuzzy classi er) with good generalization ability in a high dimensional feature space has been an active research topic for a long time. As a powerful machine learning approach for pattern recognition problems, support vector machine (SVM) is known to have good generalization ability. More importantly, an SVM can work very well on a high (or e...
متن کاملATR Performance Prediction Using Attributed Scattering Features
We present a method for estimating classi cation performance of a model-based synthetic aperture radar (SAR) automatic target recognition (ATR) system. Target classi cation is performed by comparing a feature vector extracted from a measured SAR image chip with a feature vector predicted from a hypothesized target class and pose. The feature vectors are matched using a Bayes likelihood metric t...
متن کامل