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Proceedings Paper

GPU acceleration of predictiion-based lower triangular transform for lossless compression
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Paper Abstract

The prediction-based lower triangular transform (PLT) features the same de-correlation and coding gain properties as the Karhunen-Loeve transform (KLT), but with a lower design and implementational cost. Unlike KLT, PLT has the perfect reconstruction property which allows its direct use for lossless compression. Our previous work has shown that PLT is good for lossless compression of ultraspectral sounder data with several thousands of channels. As the computation involves many operations on large matrices, this work will exploit the parallel compute power of graphics processing unit (GPU) to speed up the PLT encoding scheme. The CUDA (Compute Unified Device Architecture) platform by NVidia will be used for comparison with a single threaded CPU core. The experimental result reveals that our GPU implementation of the PLT encoding scheme shows a speedup of 95x compared to its original Matlab implementation on CPU. Thus it is promising to apply the GPU-based PLT encoding scheme for ultraspectral sounder data compression.

Paper Details

Date Published: 19 October 2012
PDF: 6 pages
Proc. SPIE 8514, Satellite Data Compression, Communications, and Processing VIII, 851404 (19 October 2012); doi: 10.1117/12.931311
Show Author Affiliations
Shih-Chieh Wei, Tamkang Univ. (Taiwan)
Bormin Huang, Univ. of Wisconsin-Madison (United States)


Published in SPIE Proceedings Vol. 8514:
Satellite Data Compression, Communications, and Processing VIII
Bormin Huang; Antonio J. Plaza; Carole Thiebaut, Editor(s)

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