Multispectral loss-less compression using approximation methods

— The large size of multispectral data files is currently a major issue in multispectral imaging. The transmission of multispectral data over networks, as well as the storage of large archives, are strongly limited, so that a clear need for good compression methods arises. In this paper, we explore the possibility of loss-less compression for multispectral data through a number of approximation methods that operate on the spectral domain. To evaluate the performance of these methods, we apply them to a representative spectra database, and consider the corresponding decrease in information entropy as well as the classical file size ratio. Keywords – multispectral imaging; multispectral compression; loss-less compression

• Type: Conference
• Year: 2005
• Where: ICIP
• Authors: Paolo Pellegri, Gianluca Novati, Raimondo Schettini
• Keywords: ICIP 2005, Image Processing, Multispectral, Multispectral Data, Multispectral Imaging