Goal of this work is to investigate lossy compression methodologies from the viewpoint of spectral distortion introduced in hyperspectral pixel vectors, besides that of radiometric distortion. The main result of this analysis is that, for a given compression ratio, near-lossless methods, i.e., with constrained pixel error, either absolute or relative, are more suitable for preserving the spectral discrimination capability among pixel vectors, which is perhaps the main source of spectral information. Therefore, whenever a lossless compression is not practicable, near-lossless compression is recommended in such applications where spectral quality is crucial.
Spectral Distortion Evaluation in Lossy Compression of Hyperspectral Imagery
Aiazzi B;Alparone L;Baronti S;Lastri C;Santurri L;Selva M
2003
Abstract
Goal of this work is to investigate lossy compression methodologies from the viewpoint of spectral distortion introduced in hyperspectral pixel vectors, besides that of radiometric distortion. The main result of this analysis is that, for a given compression ratio, near-lossless methods, i.e., with constrained pixel error, either absolute or relative, are more suitable for preserving the spectral discrimination capability among pixel vectors, which is perhaps the main source of spectral information. Therefore, whenever a lossless compression is not practicable, near-lossless compression is recommended in such applications where spectral quality is crucial.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
