Goal of the present work is to investigate and compare different compression methodologies from the view-point of spectral distortion introduced in hyper-spectral pixel vectors. The main result of this analysis is that, for a given compression ratio, near-lossless methods, either MAD- or PMAD-constrained, are more suitable for preserving the spectral discrimination capability among pixel vectors, which is the principal outcome of spectral information. Therefore, whenever a lossless compression is not practicable, the use of near-lossless compression is recommended in such application where spectral quality is a crucial point.
Impact of irreversible data compression on spectral distortion of hyper-spectral data / Aiazzi, B; Baronti, S; Santurri, L; Selva, M; Alparone, L. - STAMPA. - (2003), pp. 107-112. (Intervento presentato al convegno 22nd Symposium of the European-Association-of-Remote-Sensing-Laboratories tenutosi a Prague, Czech Republic nel 4 - 6 June 2002).
Impact of irreversible data compression on spectral distortion of hyper-spectral data
ALPARONE, LUCIANO
2003
Abstract
Goal of the present work is to investigate and compare different compression methodologies from the view-point of spectral distortion introduced in hyper-spectral pixel vectors. The main result of this analysis is that, for a given compression ratio, near-lossless methods, either MAD- or PMAD-constrained, are more suitable for preserving the spectral discrimination capability among pixel vectors, which is the principal outcome of spectral information. Therefore, whenever a lossless compression is not practicable, the use of near-lossless compression is recommended in such application where spectral quality is a crucial point.I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.