Binary coding for hyperspectral imagery

Abstract

Binary coding is one of simplest ways to characterize spectral features. One commonly used method is a binary coding-based image software system, called Spectral Analysis Manager (SPAM) for remotely sensed imagery developed by Mazer et al. For a given spectral signature, the SPAM calculates its spectral mean and inter-band spectral difference and uses them as thresholds to generate a binary code word for this particular spectral signature. Such coding scheme is generally effective and also very simple to implement. This paper revisits the SPAM and further develops three new SPAM-based binary coding methods, called equal probability partition (EPP) binary coding, halfway partition (HP) binary coding and median partition (MP) binary coding. These three binary coding methods along with the SPAM well be evaluated for spectral discrimination and identification. In doing so, a new criterion, called a posteriori discrimination probability (APDP) is also introduced for performance measure.