Onboard Image Processing System for Hyperspectral Sensor

Sensors

Hiroki Hihara⁵  Kotaro Moritani⁵  Masao Inoue⁵  Yoshihiro Hoshi⁵  Akira Iwasaki⁶  Jun Takada³  Hitomi Inada⁴  Makoto Suzuki²  Taeko Seki⁷  Satoshi Ichikawa⁷  Jun Tanii¹ 

[1] Japan Space Systems, 3-5-8 Shibakoen, Minato-ku, Tokyo 105-0011, Japan; E-Mail:;Institute of Space Astronautical Science (ISAS), Japan Aerospace Exploration Agency (JAXA), 3-1-1 Yoshinodai, Chuo-ku, Sagamihara, Kanagawa 252-5210, Japan; E-Mail:;Central Research Laboratory, NEC Corporation, 1753, Shimonumabe, Nakahara-Ku, Kawasaki, Kanagawa 211-8666, Japan; E-Mail:;Space Systems Division, NEC Corporation, 1-10, Nisshin-cho, Fuchu, Tokyo 183-8551, Japan; E-Mail:;NEC Space Technologies, Ltd., 1-10, Nisshin-cho, Fuchu, Tokyo 183-8551, Japan; E-Mails:;Research Center for Advanced Science and Technology, the University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8904, Japan; E-Mail:;Aerospace Research and Development Directorate, Japan Aerospace Exploration Agency (JAXA), 2-1-1 Sengen, Tsukuba, Ibaraki 305-8505, Japan; E-Mails:

关键词: hyperspectral sensor;    Golomb-Rice coding;    hierarchical prediction;    lossless image compression;    predictive coding;    resolution scaling;    onboard correction;    smile correction;   

DOI  :  10.3390/s151024926

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.