Detection from hyperspectral images compressed using rate distortion and optimization techniques under JPEG2000 part 2

This paper studies the effect of different bit rate allocation strategies in JPEG2000 part 2 compression of hyperspectral data on the results of background classification. We compare the traditional bit rate allocation approach, based on the high bit rate quantizer approach, with the rate distortion optimal (RDO) approach that produces a bit rate allocation optimal in the mean squared error (MSE) sense. The experiments show that for relatively low bit rates both rate allocation strategies perform with excellent and almost similar accuracy (96% at 0.125 bpppb). However, at very low bit rates, RDO outperforms (90% at 0.0375 bpppb) the high bit rate quantizer approach in terms of detection. The experiments also confirm that RDO bit rate allocation achieves a lower MSE than the high bit rate quantizer model approach.