In this chapter, we consider lossy compression of multichannel images acquired by remote sensing systems. Two main features of such data are taken into account. First, images contain inherent noise that can be of different intensity and type. Second, there can be essential correlation between component images. These features can be exploited in 3D compression that is demonstrated to be more efficient than component-wise compression. The benefits are in considerably higher compression ratio attained for the same or even less distortions introduced. It is shown that important performance parameters of lossy compression can be rather easily and accurately predicted.
Vladimir LukinIrina VasilyevaSergey KrivenkoFangfang LiSergey AbramovOleksii RubelBenoît VozelKacem ChehdiKaren Egiazarian
Vladimir LukinAlexander ZemliachenkoSergey KrivenkoBenoît VozelKacem Chehdi
Vladimir LukinSergey AbramovRuslan KozhemiakinBenoît VozelB. DjurovicIgor Djurović
Vladimir LukinNikolay PonomarenkoAlexander A. ZelenskyAndriy KurekinK.V. Lever