Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
Feature Selection: Evaluation, Application, and Small Sample Performance
IEEE Transactions on Pattern Analysis and Machine Intelligence
Remote Sensing Digital Image Analysis: An Introduction
Remote Sensing Digital Image Analysis: An Introduction
| Hi-index | 0.00 |
This manuscript presents a novel methodology for band selection (BS) for hyperspectral sensors (HSs) tailored to target detection applications. The new selection strategy chooses a subset of bands that maximizes an objective functionsuitable for target detection. In particular, it extracts the subset of bands that optimizes the probability of detecting a target (PD) in a given background, for a fixed probability of false alarm (PFA). An experimental example of the methodology effectiveness is given. In the example the well-known Adaptive Matched Filter (AMF) detector and synthetic data derived from an AVIRIS hyperspectral image are considered. The results obtained show that the the new strategy outperforms two existing BS algorithms.