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Sensors 2015, 15(10), 24926-24944;

Onboard Image Processing System for Hyperspectral Sensor

NEC Space Technologies, Ltd., 1-10, Nisshin-cho, Fuchu, Tokyo 183-8551, Japan
Research Center for Advanced Science and Technology, the University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8904, Japan
Central Research Laboratory, NEC Corporation, 1753, Shimonumabe, Nakahara-Ku, Kawasaki, Kanagawa 211-8666, Japan
Space Systems Division, NEC Corporation, 1-10, Nisshin-cho, Fuchu, Tokyo 183-8551, Japan
Institute of Space Astronautical Science (ISAS), Japan Aerospace Exploration Agency (JAXA), 3-1-1 Yoshinodai, Chuo-ku, Sagamihara, Kanagawa 252-5210, Japan
Aerospace Research and Development Directorate, Japan Aerospace Exploration Agency (JAXA), 2-1-1 Sengen, Tsukuba, Ibaraki 305-8505, Japan
Japan Space Systems, 3-5-8 Shibakoen, Minato-ku, Tokyo 105-0011, Japan
Author to whom correspondence should be addressed.
Academic Editor: Caterina Ciminelli
Received: 13 May 2015 / Revised: 23 August 2015 / Accepted: 15 September 2015 / Published: 25 September 2015
(This article belongs to the Special Issue Photonic Sensors in Space)
Full-Text   |   PDF [1507 KB, uploaded 25 September 2015]   |  


Onboard image processing systems for a hyperspectral sensor have been developed in order to maximize image data transmission efficiency for large volume and high speed data downlink capacity. Since more than 100 channels are required for hyperspectral sensors on Earth observation satellites, fast and small-footprint lossless image compression capability is essential for reducing the size and weight of a sensor system. A fast lossless image compression algorithm has been developed, and is implemented in the onboard correction circuitry of sensitivity and linearity of Complementary Metal Oxide Semiconductor (CMOS) sensors in order to maximize the compression ratio. The employed image compression method is based on Fast, Efficient, Lossless Image compression System (FELICS), which is a hierarchical predictive coding method with resolution scaling. To improve FELICS’s performance of image decorrelation and entropy coding, we apply a two-dimensional interpolation prediction and adaptive Golomb-Rice coding. It supports progressive decompression using resolution scaling while still maintaining superior performance measured as speed and complexity. Coding efficiency and compression speed enlarge the effective capacity of signal transmission channels, which lead to reducing onboard hardware by multiplexing sensor signals into a reduced number of compression circuits. The circuitry is embedded into the data formatter of the sensor system without adding size, weight, power consumption, and fabrication cost. View Full-Text
Keywords: hyperspectral sensor; Golomb-Rice coding; hierarchical prediction; lossless image compression; predictive coding; resolution scaling; onboard correction; smile correction hyperspectral sensor; Golomb-Rice coding; hierarchical prediction; lossless image compression; predictive coding; resolution scaling; onboard correction; smile correction

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Hihara, H.; Moritani, K.; Inoue, M.; Hoshi, Y.; Iwasaki, A.; Takada, J.; Inada, H.; Suzuki, M.; Seki, T.; Ichikawa, S.; Tanii, J. Onboard Image Processing System for Hyperspectral Sensor. Sensors 2015, 15, 24926-24944.

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