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Proceedings Paper

A hyperspectral images compression algorithm based on 3D bit plane transform
Author(s): Lei Zhang; Libin Xiang; Sam Zhang; Shengxue Quan
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Paper Abstract

According the analyses of the hyper-spectral images, a new compression algorithm based on 3-D bit plane transform is proposed. The spectral coefficient is higher than the spatial. The algorithm is proposed to overcome the shortcoming of 1-D bit plane transform for it can only reduce the correlation when the neighboring pixels have similar values. The algorithm calculates the horizontal, vertical and spectral bit plane transform sequentially. As the spectral bit plane transform, the algorithm can be easily realized by hardware. In addition, because the calculation and encoding of the transform matrix of each bit are independent, the algorithm can be realized by parallel computing model, which can improve the calculation efficiency and save the processing time greatly. The experimental results show that the proposed algorithm achieves improved compression performance. With a certain compression ratios, the algorithm satisfies requirements of hyper-spectral images compression system, by efficiently reducing the cost of computation and memory usage.

Paper Details

Date Published: 26 October 2010
PDF: 5 pages
Proc. SPIE 7658, 5th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optoelectronic Materials and Devices for Detector, Imager, Display, and Energy Conversion Technology, 76585R (26 October 2010); doi: 10.1117/12.867625
Show Author Affiliations
Lei Zhang, Xi'an Institute of Optics and Precision Mechanics (China)
Academy of Opto-Electronics (China)
Shenyang Institute of Aeronautical Engineering (China)
Libin Xiang, Academy of Opto-Electronics (China)
Sam Zhang, Academy of Opto-Electronics (China)
Shengxue Quan, Academy of Opto-Electronics (China)


Published in SPIE Proceedings Vol. 7658:
5th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optoelectronic Materials and Devices for Detector, Imager, Display, and Energy Conversion Technology
Yadong Jiang; Bernard Kippelen; Junsheng Yu, Editor(s)

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