Comparative Study of Data Compression Methods for Large Aperture Static Imaging Spectrometer.

Abstract

Facing the problem of choosing different data source as compressing object results in different compression effect, several techniques are investigated to explore a better data source which can reduce the loss of image and spectral information while getting higher compression ratio in the compression work of the large aperture static imaging spectrometer. In this paper the optical path difference dimension data source of LASIS was proposed after analyzing the characteristic of LASIS and then compared with the LASIS and LAMIS data source in detail. The SWIR data collected with the principle prototype of LASIS were used in our experiment. Firstly, three forms of data sources were extracted after detailedly introducing their data characteristic and extracting methods. Secondly, the mature algorithms in engineering JPEG and JPEG2000 were employed to compress and reconstruct the three forms of data sources respectively. Finally, the compression effect was evaluated in the aspect of image content, interference dimension, spectral dimension and compression ratio respectively, and the original spectral curves of three materials choosing from the field of view and those after reconstruction were extracted next, then the loss of spectral information of these three materials were measured by using the SA (Spectral Angle) and RQE (Relative Quadratic Error) values of the spectral curves to evaluate the compression effect. It is demonstrated that using the optical path difference dimension data as compressing object shows obvious advantages compared with LASIS and LAMIS, which achieves a combination of higher compression ratio, lower mean square error, lower peak signal noise ratio and less information loss that is competitive with the best results from the literature. The results show that the proposed optical path difference dimension data source has good performance in preserving the spatial and spectral information during the compression of LASIS than the other two common forms data sources of LASIS.