Noise reduction and analysis for Chang'E-1 Imaging Interferometer (IIM) data

Abstract

Imaging Interferometer (IIM) aboard Chang'E-1 is a Fourier transform imaging spectrometer, with goals to analyze the abundance and distribution of chemical elements on the lunar surface. IIM data suffer from various degradations, which will lead to misleading interpretations of IIM data and inaccuracy of subsequent applications. In this paper, we introduced a noise reduction method based on low-rank matrix decomposition theory. The restoration results are expected to have a better performance in image quality and spectral signatures according to visual and quantitative assessments. Meanwhile, we analyze the characteristic of the noise separated from IIM data using top spectral view of noise cube. The preliminary analysis of the noise characteristics contribute to optimize the data preprocessing of IIM data such as spectrum reconstruction and radiometric correction.