Lossless Compression of Ultraspectral Sounder Data
Bormin Huang, Alok Ahuja, Hung-Lung Allen Huang · Kluwer Academic Publishers eBooks · 2006
5 ConclusionsThe compression of ultraspectral sounder data is better to be lossless or near-lossless to avoid potential degradation of the geophysical retrieval in the associated ill-posed problem. Transform-based, prediction-based, and clustering-based methods for lossless compression of ultraspectral sounder data have been presented. It is shown that the compression ratios of ultraspectral sounder data via the standard state-of-the-art algorithms (e.g. 3D SPIHT, 2D JPEG2000, 2D CALIC, 2D JPEG-LS etc.) can be significantly improved when combining the BAR preprocessing scheme. We also report the promising compression results for the ultraspectral sounder data using various approaches such as lossless PCA and Predictive Partitioned Vector Quantization (PPVQ).