Abstract
The Karhunen–Loeve transform (KLT) is the optimal unitary transform that yields the maximum coding gain. The prediction-based lower triangular transform (PLT) features the same decorrelation and coding gain properties as KLT but with lower complexity. Unlike KLT, PLT has the perfect reconstruction property which allows its direct use for lossless compression. In this paper, we apply PLT to carry out lossless compression of the ultraspectral sounder data. The experiment on the standard ultraspectral test dataset of ten AIRS digital count granules shows that the PLT compression scheme compares favorably with JPEG-LS, JPEG2000, LUT, SPIHT, and CCSDS IDC 5/3.
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Wei, SC., Huang, B. (2012). Ultraspectral Sounder Data Compression by the Prediction-Based Lower Triangular Transform. In: Huang, B. (eds) Satellite Data Compression. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-1183-3_7
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DOI: https://doi.org/10.1007/978-1-4614-1183-3_7
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