Application of independent component analysis to lossless compression of 3D ultraspectral sounder data

Abstract

The ultraspectral sounder data is known for its huge size and sensitivity to noise in ill-posed retrieval of geophysical parameters. It is thus desired to be lossless compressed for transfer and storage. The independent component analysis (ICA) features a decorrelation capability beyond second-order moments. It was traditionally used in blind source separation. Recently ICA has seen its use in lossy compression of hyperspectral imager data. It was mainly used to reduce the dimension of data for target detection. Meanwhile report of ICA in lossless compression of image data was also seen where ICA was used to reduce the redundancy of coefficients in wavelet lifting schemes. In this paper we will explore the use of ICA in lossless compression of ultraspectral sounder data. The compression result shows that ICA compares favorably with BZIP2, CALIC, JPEG2000, SPIHT, JPEG-LS, and CCSDS IDC 5/3 for the standard data set of 10 AIRS granules.