大孔径静态干涉成像光谱仪数据源选择对压缩效果影响的研究

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

针对实际工程应用中存在的大孔径静态干涉成像光谱仪(large aperture static imaging spectrometer,LASIS)的数据压缩问题,根据LASIS的成像特点,在详细分析其数据特性之后,提出了基于光程差维数据源的压缩,并与以往的LASIS和LAMIS数据源压缩进行对比研究。选择不同的数据源获得的压缩效果不同,为了更合理的选择LASIS数据源,降低压缩算法带来的图像和光谱损失,实验以LASIS原理样机推扫获得的短波红外数据作为研究对象,在详细介绍了三种数据的数据特点以及提取方法之后,变换得到上述三种形式的数据源,采用工程中成熟应用的JPEG和JPEG2000算法对三种数据源分别进行逐帧压缩和重建,然后对压缩效果在图像维、干涉维和光谱维以及压缩比进行了详细的对比分析,并提取视场中三种目标物质的光谱曲线,对压缩前后它们的光谱信息损失进行了度量。实验结果表明,相较于采用LASIS和LAMIS数据源作为压缩对象,以LASIS光程差维数据作为压缩对象,无论是在图像维、干涉维还是光谱维的压缩评价标准下都表现出明显的优越性:同样的压缩方案下,基于光程差维数据源的压缩能在获得较高压缩比的同时获得更低的均方误差和更高的峰值信噪比,且对光谱信息的损失也是三种数据源中最小的。

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.