Lossless data compression for infrared hyperspectral sounders: an update

Bormin Huang; Hung-Lung Allen Huang; Alok Ahuja; Timothy J. Schmit; Roger W. Heymann

doi:10.1117/12.560404

14 October 2004 Lossless data compression for infrared hyperspectral sounders: an update

Bormin Huang, Hung-Lung Allen Huang, Alok Ahuja, Timothy J. Schmit, Roger W. Heymann

Proceedings Volume 5548, Atmospheric and Environmental Remote Sensing Data Processing and Utilization: an End-to-End System Perspective; (2004) https://doi.org/10.1117/12.560404
Event: Optical Science and Technology, the SPIE 49th Annual Meeting, 2004, Denver, Colorado, United States

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.

Citation Download Citation

Bormin Huang, Hung-Lung Allen Huang, Alok Ahuja, Timothy J. Schmit, and Roger W. Heymann "Lossless data compression for infrared hyperspectral sounders: an update", Proc. SPIE 5548, Atmospheric and Environmental Remote Sensing Data Processing and Utilization: an End-to-End System Perspective, (14 October 2004); https://doi.org/10.1117/12.560404

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