Is there a best hyperspectral detection algorithm?

Abstract

A large number of hyperspectral detection algorithms have been developed and used over the last two decades. Some algorithms are based on highly sophisticated mathematical models and methods; others are derived using intuition and simple geometrical concepts. The purpose of this paper is threefold. First, we discuss the key issues involved in the design and evaluation of detection algorithms for hyperspectral imaging data. Second, we present a critical review of existing detection algorithms for practical hyperspectral imaging applications. Finally, we argue that the "apparent" superiority of sophisticated algorithms with simulated data or in laboratory conditions, does not necessarily translate to superiority in real-world applications.