Satellite Hyperspectral Imagery Compression Algorithm Based on Adaptive Band Regrouping

Hyperspectral image from satellite is important for earth observation and military reconnaissance. However there exists big contradictory between the transmission capacity of satellite channel and large amount hyperspectral data. There are spatial and spectrum redundancy in hyperspectral image. As to exploit spectrum correlation sufficiently, it must be to pre-process hyperspectral image. In this paper, we propose a novel acceptable complexity lossy hyperspectral image compression scheme which combines the prediction based on adaptive band regrouping and JPEG2000-based coding algorithm. The regrouping includes band classification and reference frame selection. Our experiments show that the proposed approach has a good performance in quality and fidelity. It is effective and not complicated, which may be a good choice for hyperspectral compression in the embedded processor of satellite platform