Special Section on Satellite Data Compression

Constant coefficients linear prediction for lossless compression of ultraspectral sounder data using a graphics processing unit

[+] Author Affiliations
Jarno Mielikainen

Yonsei University, School of Electrical and Electronic Engineering, 134 Sinchon-dong, Seoul, 120-749 Republic of Korea

Risto Honkanen

University of Oulu, Department of Information Processing Science, Kajaani FI-87101 Finland

Bormin Huang

University of Wisconsin-Madison, Space Science and Engineering Center, 1225 West Dayton Street, Madison, WI 53706

Pekka Toivanen

University of Eastern Finland, School of Computing, Kuopio FI-70211 Finland

Chulhee Lee

Yonsei University, School of Electrical and Electronic Engineering, 134 Shinchon-Dong, Seodaemoon-Gu, Seoul 120-749 Republic of Korea

J. Appl. Remote Sens. 4(1), 041774 (September 15, 2010). doi:10.1117/1.3496907
History: Received December 14, 2009; Revised July 2, 2010; Accepted September 2, 2010; September 15, 2010; Online September 15, 2010
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Abstract

The amount of data generated by ultraspectral sounders is so large that considerable savings in data storage and transmission bandwidth can be achieved using data compression. Due to this large amount of data, the data compression time is of utmost importance. Increasing the programmability of the commodity Graphics Processing Units (GPUs) offer potential for considerable increases in computation speeds in applications that are data parallel. In our experiments, we implemented a spectral image data compression method called Linear Prediction with Constant Coefficients (LP-CC) using NVIDIA's CUDA parallel computing architecture. LP-CC compression method represents a current state-of-the-art technique in lossless compression of ultraspectral sounder data. The method showed an average compression ratio of 3.39 when applied to publicly available NASA AIRS data. We achieved a speed-up of 86 compared to a single threaded CPU version. Thus, the commodity GPU was able to significantly decrease the computational time of a compression algorithm based on a constant coefficient linear prediction.

© 2010 Society of Photo-Optical Instrumentation Engineers

Citation

Jarno Mielikainen ; Risto Honkanen ; Bormin Huang ; Pekka Toivanen and Chulhee Lee
"Constant coefficients linear prediction for lossless compression of ultraspectral sounder data using a graphics processing unit", J. Appl. Remote Sens. 4(1), 041774 (September 15, 2010). ; http://dx.doi.org/10.1117/1.3496907


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