In this paper we review the Spectral oriented Least SQuares (SLSQ) algorithm : an efficient and low complexity algorithm for Hyper spectral Image loss less compression, presented in [2]. Subsequently, we consider two important measures : Pearson's Correlation and Bhattacharyya distance and describe a band ordering approach based on this distances. Finally, we report experimental results achieved with a Java-based implementation of SLSQ on data cubes acquired by NASA JPL's Airborne Visible/Infrared Imaging Spectrometer (AVIRIS).