Lossless data compression for infrared hyperspectral sounders: an update

Abstract

The compression of hyperspectral sounder data is beneficial for more efficient archive and transfer given its large 3-D volume. Moreover, since physical retrieval of geophysical parameters from hyperspectral sounder data is a mathematically ill-posed problem that is sensitive to the error of the data, lossless or near-lossless compression is desired. This paper provides an update into applications of state-of-the-art 2D and 3D lossless compression algorithms such as 3D EZW, 3D SPIHT, 2D JPEG2000, 2D JPEG-LS and 2D CALIC for hyperspectral sounder data. In addition, in order to better explore the correlations between the remote spectral regions affected by the same type of atmospheric absorbing constituents or clouds, the Bias-Adjusted Reordering (BAR) scheme is presented which reorders the data such that the bias-adjusted distance between any two neighboring vectors is minimized. This scheme coupled with any of the state-of-the-art compression algorithms produces significant compression gains.

Ultraspectral sounder data compression review

“…Moreover, the bias adjustment has reduced the dynamic range of the reordered data as visualized by the reduction of grayscale intensities. Following the BAR preprocessing, significant compression gains have been reported on 3D SPIHT, 2D JPEG2000, 2D JPEG-LS and 2D CALIC in (Huang, et al, 2004b). Investigations are underway for applying the BAR scheme to the 3D versions of these schemes.…”

Lossless Compression of Ultraspectral Sounder Data

“…Moreover, the bias adjustment has reduced the dynamic range of the reordered data as visualized by the reduction of grayscale intensities. Following the BAR preprocessing, significant compression gains have been reported on 3D SPIHT, 2D JPEG2000, 2D JPEG-LS and 2D CALIC in [28]. Investigations are underway for applying the BAR scheme to the 3D versions of these schemes.…”